Wipro Limited

International Business Machines Corporation

Oracle International Corporation

Anumana, Inc.

Mayank Sharma

Rakesh Barve

Uddeshya Upadhyay

Ashim Prasad

Anuj Gupta

Sairam Bade

Matheen Shaik

Buland Khan

Aditi Bhattacharya

Chiranjeevi Bhagavan

Gaurav Kumar Arora

Vinay Nair

Dhanavel Karthikeyan

Sandeep Dixit

Nitin Tewari

A computer-implemented method, according to one embodiment, includes analyzing application details associated with a plurality of different timestamp intervals, in response to a determination, from results of analyzing runtime information associated with an application failure event and/or sub-par runtime performance that occurs during a first operational run cycle of an application, that the failure event and/or sub-par runtime performance is caused by a Non-Functional Requirement (NFR) issue. In response to a determination that a first of the timestamp intervals falls within a timestamp associated with the application failure event and/or sub-par runtime performance, first pattern information about the application details associated with the first timestamp interval is collected. The method further includes applying the first pattern information to a weightage algorithm. In response to a determination that test coverage gaps exist in a predetermined collection of test cases, test cases are created based on the first pattern information.

Determining non-functional requirements (NFR) from a run time environment and incorporating into a development cycle

A system for training machine learning models with unlabeled electrocardiogram signals, the system including a memory containing instructions configurating a processor to receive a plurality of electrocardiogram (ECG) data in a textual format, create one or more overlapping temporal patches from the plurality of ECG data, mask at least one temporal patch from the one or more overlapping temporal patches, pretrain an ECG machine learning model to predict the at least one masked temporal patch from the one or more overlapping temporal patches, adjust one or more parameter values of the ECG machine learning model as a function of the at least one predicted masked temporal patch and the at least one masked temporal patch and train the ECG machine learning model as a function of the one or more parameter values and a labeled set of ECG training data.

Systems and methods for training machine learning models using unlabeled electrocardiogram data

A plurality of tickets can be received. A pattern pertaining to an issue with an application can be determined by at least one artificial neural network. The pattern can be indicated among at least a portion of the plurality of tickets. The portion of the plurality of tickets can be grouped into a group comprising a primary ticket and at least one secondary ticket. Automation steps can be accessed from a database. The automation steps can be implemented to resolve the issue for the primary ticket. Responsive to the resolving the issue by implementing the automation steps from the database for the primary ticket, the secondary ticket can be closed.

Machine learning of pattern category identification for application component tagging and problem resolution

Embodiments of present disclosure discloses system and method for conversion of structured database into unstructured database. Initially, structured database and database descriptor is retrieved in distributed environment. Structured database comprises data fields, and each of the data fields corresponds to financial transaction. Optimized target data model is generated for storing data in the unstructured database, based on at least one of database objects extracted from data fields of structured database, and pre-defined conversion rules. Further, a Blockchain comprising blocks corresponding to each financial transaction of structured database. Each of the blocks comprise at least one of extracted database object. Conversion of the database object of each of the blocks into data fields of unstructured database is performed based on optimized target data model and notification corresponding to data fields of unstructured database is generated which are associated with discrepancies corresponding to the financial transaction.

Method and system for data conversion and data model optimization

Disclosed herein is method and system for preventing traffic congestion of vehicles. Real-time traffic data related to a primary route being traversed by a vehicle, and location information of the vehicle are collected and analyzed to determine one or more alternative routes having less traffic congestion than the primary route. Further, congestion weightages are assigned to each of the alternative routes to identify an optimal route, having least traffic congestion, among the alternative routes. The optimal route is recommended to a user of the vehicle, thereby preventing traffic congestion. In an embodiment, the present method obtains the real-time traffic data directly from a computing device and/or one or more sensors integrated in the vehicle, and thereby accurately identifies the optimal route for the vehicle.

Method and system for preventing traffic congestion of vehicles

A method and system for synchronization of Relational Database Management System (RDBMS) to non-Structured Query Language (noSQL) database receives a user request and associated predefined business logic from a user device for retrieving one or more transactional data and synchronizes the RDBMS to the noSQL database based on the predefined business logic. The database synchronization system segregates the predefined business logic into one or more processing divisions and assigning the one or more processing divisions to the RDBMS and the noSQL database. Further, the noSQL database retrieves data related to one or more elements of one or more tables related to the one or more transactional data from the RDBMS. Thereafter, the noSQL database transforms the retrieved data and provide to the database synchronization system. Finally, database synchronization system provides transformed data received from the noSQL database to the user device.

Method and system for synchronization of relational database management system to non-structured query language database

In accordance with accordance, described herein is a system and method for providing a cloud service for distributing enterprise data to data consumers for reuse. The cloud service can include a generic connector interface configured to retrieve enterprise data from a PaaS service, and a plurality of services used for categorizing the enterprise data, managing identities of the data consumers, configuring data access rules, and masking the enterprise data. A plurality of representational state transfer (REST) application programming interfaces (APIs) can be exposed by the cloud service for a tenant to manage the enterprise data and data consumers, and for data consumers to subscribe to the enterprise data. The system allows a PaaS tenant to distribute enterprise data from a PaaS service to a plurality of data consumers securely and scalably.

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Bengaluru, India

Mayank Sharma