Conduent Business Services, LLC

Sriranjani Ramakrishnan

Arun Rajkumar

Shourya Roy

Himanshu Sharad Bhatt

Narayanan Unny

Shisagnee Banerjee

Rishabh Singh

Kowshik Chilamkurthi

Prateek Yadav

Systems, methods, and processing nodes determine and perform preventive maintenance on a transport vehicle in a transportation system. The method includes extracting features for previous incidents that have occurred to a plurality of transport vehicles in the transportation system. The method also includes determining a criticality of types of incidents based on the features extracted. The method includes predicting, based on the criticality of types of incidents and the features extracted, details of at least one future incident for a first transport vehicle from the plurality of transport vehicles. The details include a predicted type of the at least one future incident, a predicted time of the at least one future incident, and a predicted criticality of the at least one future incident. Additionally, the method includes performing a prescriptive action for the first transport vehicle to mitigate the at least one future incident in the first transport vehicle.

Modelling operational conditions to predict life expectancy and faults of vehicle components in a fleet

The disclosed embodiments illustrate a domain adaptation method for learning transferable feature representations from a source domain for a target domain. The method includes receiving real-time input data comprising labeled instances of the source domain and unlabeled instances of the target domain from a computing device. The method further includes determining source specific representation corresponding to the source domain and a common representation shared between the source domain and the target domain. Based on a positive contribution from the source specific representation and the common representation, the labeled instances of the source domain are classified. The method further includes training a generalized classifier based on a positive contribution from the common representation. The method further includes automatically performing text classification on the unlabeled instances of the target domain based on the trained generalized classifier. The result of the text classification is rendered at a user interface of the computing device.

Method and system for text classification based on learning of transferable feature representations from a source domain

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TamiNadu, India

Sriranjani Ramakrishnan