Mahindra Satyam - Intellectual Properties

U.S. Pat. No. 7,496,655 : System and method for static and dynamic load analyses of communication network
The proposed system defines a predictive real-time Service Level Agreements (SLAs) monitoring system by:

A detailed analysis of traffic flows with reduced monitor-data flow across network; and
A suitable combination of offline and real-time processing of historical and current traffic data.

In order to be able to undertake a detailed analysis without significantly impacting the network throughput, the system analyzes the historical traffic patterns of a typical Provider's network to determine a set of critical SLAs. An in-depth analysis of traffic is performed by creating a unique network parent probe for every critical SLA and the parent probe spawns an optimal number of intelligent master and slave probes based on a regionalization procedure. The online overload monitoring system analyzes the gathered data from the master and slave probes to:

Forecast future violations of the SLA under consideration based on multiple forecast models; and
Generate operator SLA violation alarms.

U.S. Pat. No. 7,415,527: System and method for piecewise streaming of video using a dedicated overlay network
The main challenge in providing video on demand service is to meet the quality of service requirements under the conditions when both server and network are loaded. Disclosed is a system and method for meeting this challenge by using a streaming overlay network with edge and core nodes, by determining the best possible path for bulk copying of a video data based on location information of the nodes thereby distributing load across the network, by the simultaneous frame streaming and bulk copying of a video data, by the caching of a video data in the overlay network, and by the streaming of the video data to a client from an edge node that is close to the client.

U.S. Pat. No. 7,373,365: System and method for automatic indexing and archiving of paper documents
Enterprises deal with a lot of papers in their day-to-day activities. Many of these papers are company confidential / legal documents with a statutory requirement that they be preserved for a pre-specified number of years. During the course of time, there is a need to (a) obtain copies of these papers; and (b) modify the contents. Such frequent handling of papers may reduce the life of the papers and lead to statutory violations. A system for automatic indexing and retrieval of paper documents involves (a) storing paper documents in a secured manner in both hard and soft forms; (b) indexing of both forms of the stored paper documents; (c) retrieving soft form of a paper document for display and copying; (d) retrieving hard form of a paper document for modification and removal; (e) managing multiple versions of the paper documents; and (e) access control and audit trailing. It is essential to maintain consistency between hard and soft forms, and image processing techniques are deployed to ensure consistency between hard and soft forms. Another form of consistency that is required to be ensured is the correct cataloging and indexing of paper documents. This is achieved by comparing input information with the contents of the cover page of a paper document to account for human input errors.

US. Pat No. 6,751,614 System and method for topic-based document analysis for information filtering
An information filtering process designed to sort through large volumes of dynamically generated textual information, incrementally learning process that learns as new text documents arrive and the user grades them by providing feedback. Text-based documents either dynamically retrieved from the Web or available in a textual repository on an Intranet are represented by applying keyword weights after capturing the user reasoning for classifying the document as relevant or irrelevant. When a new item (document) arrives, the learning agent suggests a classification and also provides an explanation by pointing out the main features (key-phrases) of the item (document) responsible for its classification. The user looks at this and provides hints by showing a list of features (key phrases) that are responsible for a particular way of classifying the document. This interaction method contributes to the learning process. The apparatus includes a feedback-based clustering scheme that models user's interest profiles, a simple neural adaptation method for leaning the cluster centers to provide personalized information filtering for information seekers.