International Business Machines Corporation

Abhay Kumar Patra

Harish Bharti

Rajesh Kumar Saxena

Sarbajit Kumar Rakshit

Rakesh Shinde

Sandeep Sukhija

Amol Ashok Dhondse

Anand Pikle

Pranshu Tiwari

Deependra Kumar Singh

Vijay Ekambaram

Saurabh Trehan

Michael L Coyne

Vrunda R Negandhi

Pradeep Pappu

Manish C Patel

Stan Kevin Daley

Balakrishnan Sreenivasan

Tao Liu

Sreenath Raghunath

Binayak Dutta

Zheng Xie

Atul Kumar Thapliyal

Sanjib Choudhury

Ravi Kumar V Mandalika

Jayant Kumar Sinha

Joy Patra

Anshul Chetal

Vaibhav Mayuresh Shah

Sreeranjini R Seetharam

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.

Data swap prevention in distributed computing environments based on mapping among global user identification, correlation identification and thread identification

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.

Outage restoration time prediction during weather events and optimized solutions for recovery

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.

Private cloud user insight privacy

Methods, computer program products, and systems are presented. The methods include, for instance: obtaining domain data sources on a monolith database operating in a subject domain. Entities and relations of the monolith database are identified. By decomposing the entities of the monolith database for key entities in the subject domain, entities for a distributed database that is functionally equivalent to the monolith database are identified. Transactions performed on the monolith database and the entities of the distributed database involved therein are identified and the transactions are decomposed for the distributed database. Silhouette clustering on the distributed database regarding aspects of performance, scalability, and availability that improves the aspects of the distributed database over the monolith database is performed and the distributed database is checked for eventual consistency amongst the distributed database and one or more replicas of the distributed database before deployed to replace the monolith database.

Monolith database to distributed database transformation

A method, computer program product, and a system where a processor(s) obtains a universe of social media items posted to a social media platform at a given time. The processor(s) determines a likelihood of each item of the universe of social media items becoming viral by linking each item of the universe to a breakout pattern based on predefined dimensions and bucketing each item into a defined grouping by a measure of anticipated virality of the item. The processor(s) applies a susceptible-infected-recovered (SIR) model as a differential equation to the bucketed items to determine an equilibrium and one or more breakout points. The processor(s) determines if a social media item will become viral based on whether the item matches at least one or the one or more breakout points.

Digital modeling and prediction for spreading digital data

Techniques for text evaluation are provided. A curated dataset comprising a plurality of textual documents is received. A tree of classifiers is trained, based on the curated dataset, to identify use cases. A feature graph model is generated, based on the curated dataset, to determine textual similarity. A new document is received, and a plurality of requirements is extracted from the new document. For each requirement, one or more vector scores are generated by evaluating the requirement using the tree of classifiers, one or more feature scores are generated by evaluating the requirement using the feature graph model, and one or more use cases are identified for the new textual document based on the one or more vector scores and the one or more feature scores. An implementation is generated for the new document based on the one or more use cases.

Cognitive analysis to generate and evaluate implementation plans

A system and method for managing the provisioning of electricity to an electric vehicle includes identifying an electric vehicle when the electric vehicle connects to a charging point; determining whether the electric vehicle is associated with a smart contract; validating the smart contract associated with the electric vehicle; creating a charging transaction for charging the electric vehicle; and applying the smart contract associated with the electric vehicle against the charging transaction. The electric vehicle electricity contract management system and method may use a consensus system such as a distributed ledger system or blockchain.

Managing the provisioning of electricity for an electric vehicle

A computer system message generated by an application programming interface (API) or addressed to the API can be received. A first data sensitivity score for at least a first of a plurality of data elements in a payload of the computer system message and at least second data sensitivity score for at least a second of the plurality of data elements in the payload of the computer system message can be determined. Based on the first data sensitivity score and at least the second data sensitivity score, a differential security can be applied to the computer system message. Applying the differential security can include masking the first of the plurality of data elements and not masking the second of the plurality of data elements. The computer system message can be electronically communicated the to a destination to which the message is addressed.

Applying differential security to API message payload data elements

A power-distribution routing system of a power-transmission company receives a request to route electrical power to users through a power-grid infrastructure during a specified future period of time. The system retrieves time-stamped blockchain data that identifies past fluctuations in energy demand, service agreements between energy companies, and energy-production and demand-fulfilment histories of energy-generating sources like power plants. The system also retrieves extrinsic contextual and socioeconomic data from online sources and various business applications. An artificially intelligent cognitive framework uses a sliding-frame mechanism to infer patterns in the rate of change of user demand during past time periods similar to the period specified by the request. The system ranks each source by its demonstrated ability to satisfy the patterns of demand in consideration of the contextual data. The system directs downstream components to route energy from a mix of the highest-ranking suppliers through the grid during the specified time period.

Using blockchain to select energy-generating sources

A computer-implemented method includes: receiving, by a computing device, information regarding an application programming interface (API); classifying, by the computing device, the API using natural language classification on to a baseline taxonomy; extracting, by the computing device, information regarding features of the API based on the classifying to the baseline taxonomy; performing, by the computing device, an assessment on the API relative to other APIs within a same class as the API based on the extracting the information regarding the API features and the classifying the API; and updating, by the computing device, the API based on the performing the assessment.

API evolution and adaptation based on cognitive selection and unsupervised feature learning

A method collects from at least one power measuring device of an environment power consumption data indicating active power consumption during a timeframe by an electrical device in the environment. The method also collects operating parameter data indicating at least one operating parameter under which the electrical device operates during at least a portion of the timeframe. The method performs, based on observing an increase in power consumption of the electrical device during the timeframe, assessing extents of contribution by potential contributing factors to the increase in power consumption, the potential contributing factors including time-based degradation of the electrical device and the at least one operating parameter. The method outputs, based on the assessing, an indication of an extent of contribution of degradation of the electrical device to the increase in power consumption.

Electrical device degradation determination

A computer-implemented method of managing energy supply agreements that includes: connecting to a permissioned blockchain, the blockchain being accessible only by energy suppliers, energy transmission companies and government agencies that regulate a market for the supply of energy by energy suppliers to energy transmission companies; creating a new block for an energy purchase agreement that provides for the purchase of energy by an energy transmission company from an energy supplier; appending the new block having the energy purchase agreement to the blockchain; and responsive to the energy supplier supplying a quantity of energy to the energy transmission company in an individual energy transaction, appending the individual energy transaction as a block to the blockchain.

Managing energy purchase agreements on a blockchain

A method, system and computer program product for determining API pricing. Consumption parameters are identified using a supervised learning model. The API consumption parameters refer to any parameters that can be used to describe an API (functionality or otherwise) and can be used to compare other comparable APIs in similar domains provided by other providers. Furthermore, reference pricing is determined using machine learning using the identified API consumption parameters. Additionally, the API price is determined dynamically using the identified API consumption parameters and the determined reference pricing. An API pricing score is then derived for the API price using the supervised learning model. The API price is selected as the suggested price for the API in response to the API pricing score exceeding a threshold value. In this manner, an API price is established that reflects the true value of the API assessed by the API consumer.

API pricing based on relative value of API for its consumers

A method (and structure and computer product) of recognizing and tracking an object includes receiving image data from at least two camera sensors and analyzing the image data to determine attributes of an object detected as present in the image data. A first decision tree (DT) is developed to classify the object, based on the attributes determined from the image data. A second DT is developed to refine the first DT, wherein the second DT is used to refine the first DT by determining which attributes are most significant in the classification of the object.

Cognitive search analytics for multi-dimensional objects

A computer-implemented method includes: receiving, by a computing device, analytics data at a feeder level of a utility transmission and distribution system; generating, by the computing device, a confidence score for a feeder based on the analytics data at the feeder level; receiving, by the computing device, analytics data at a transformer level of the utility transmission and distribution system; generating, by the computing device, a confidence score for a transformer associated with the feeder based on the analytics data at the transformer level and the confidence score of the feeder; receiving, by the computing device, analytics data for customers associated with the transformer; generating, by the computing device, confidence scores for the customers based on the analytics data and the confidence score of the transformer; and outputting, by the computing device, information regarding the confidence scores for the customers for determining the effectiveness of a demand response (DR) program.

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Pune, India

Abhay Kumar Patra