Infosys Limited

Krishnamurty Sai Deepak

Radha Krishna Pisipati

Harikrishna Gandhinagara Narayana Rai

Shreyas Bettadapura Guruprasad

Karthikeyan Balaji Dhanapal

Rajesh Balakrishnan

Harikrishna G N Rai

P Radha Krishna

Uma Devi Ganugula

Jianlin Zhang

Bintu G Vasudevan

Ganesh Kumar Nunnagoppula

Arun Agrahara Somasundara

Mohsen Amini Salehi

Ann Matthew

Raj Kumar Buyya

A system and method of recognizing data in a table area from unstructured data includes a computer network, one or more processors communicatively coupled with the computer network, a storage location, and a graph-theoretic engine that receives an input stream of unstructured data associated. A table area is recognized from unstructured data, through one or more computer processors, from an input stream of unstructured data received over a computer network. One or more table headers associated with the detected one or more table areas are recognized. Further, one or more column delimiters associated with each column of the detected one or more table areas are determined. One or more tabular data associated with the detected one or more table areas are extracted. The extracted tabular data is mapped to one or more target schema to store onto a relational database.

System and method of recognizing data in a table area from unstructured data

Methods and systems for template creation for a data extraction tool. A first template is selected from a plurality of documents provided by a user. An OCR engine annotates the first template and at least one data region in the first template corresponding to a set of parameters required in a target template is identified by selecting a geometrical region on the first template. At least one interim template is created based on the identification, and the plurality of documents are analyzed using the interim template to extract data values in the data region. The documents are converted to a format compliant with the target template based on the analysis.

System and method of template creation for a data extraction tool

A method and a system for registering multi-modal brain images includes registering two or more full volumes of brain images based on a projection based reference image. The registration is based on sharing of mass in a predetermined direction such as axial, sagittal and coronal direction. After the registration of two or more brain images, a two or more partial volumes in a region of interest is registered through a modified mutual information. The modified mutual information may be a factor of an overlap rate and a weight assigned to it.

System and method for registration of brain images

Techniques for testing one or more applications running on a handheld device include: receiving, by a tester system, an error state corresponding to the one or more applications; retrieving, by the tester system, one or more tests script parameters corresponding to the error state from a database, wherein the one or more test script parameters corresponding to the error state are stored in the database; providing, by the tester system, the one or more test script parameters to an input subsystem, wherein the input subsystem is connected to the handheld device; notifying a user to provide one or more inputs corresponding to the error state, wherein the one or more test script parameters are not stored in the database; receiving, by the tester system, the one or more inputs from the user; and providing, by the tester system, the one or more inputs to the input subsystem.

Methods, systems, and computer-readable media for testing applications on a handheld device

A method and system provisions a plurality of resources of a data center. A violation risk factor for a set of low priority requests can be computed. A utilization factor of a set of activated resources of the data center shall be evaluated. According to a predefined rule base, one or more of the plurality of resources, shall be provisioned for a received high priority request, whereby the predefined rule base defines performing one or more of; a) preempting a set of virtual machines utilizing a subset of the set of activated resources, whereby the set of virtual machines is associated with the set of low priority requests; b) activating a new set of resources; and c) consolidating a plurality of virtual machines, based on the computed violation risk factor and the evaluated utilization factor.

Methods and systems for energy management in a virtualized data center

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Bengaluru, India

Krishnamurty Sai Deepak