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Bhaskar, Bangalore
Arun Kumar Bhaskar, Bangalore IN
| Patent application number | Description | Published |
|---|---|---|
| 20100153946 | DESKTOP SOURCE TRANSFER BETWEEN DIFFERENT POOLS - A method, apparatus, and system of desktop source transfer between different pools are disclosed. In one embodiment, a machine-readable medium includes determining that a transfer request is associated with a desktop source, accessing the desktop source from a source pool, and automatically transferring the desktop source from the source pool to a destination pool. | 06-17-2010 |
| 20100153950 | POLICY MANAGEMENT TO INITIATE AN AUTOMATED ACTION ON A DESKTOP SOURCE - A method, apparatus, and system of policy management to initiate an automated action on a desktop source are disclosed. In one embodiment, a machine-readable medium embodying a set of instructions is disclosed. An event is detected. The event associated with a desktop source is automatically determined. A category of the event is determined. A policy is associated to the event based on the category. The policy is applied to the desktop source. Desktop sources may be reshuffled based on the policy. The internal event may be determined as a load balancing issue in which the desktop source may reside in a pool having maximum utilization. The desktop source may be transferred to anther pool having less utilization based on the policy. | 06-17-2010 |
| 20100162237 | NETWORK ADMINISTRATION IN A VIRTUAL MACHINE ENVIRONMENT THROUGH A TEMPORARY POOL - A method, apparatus, and system of network administration in a virtual machine environment through a temporary pool are disclosed. In one embodiment, a method includes determining that a desktop source requires maintenance, creating a temporary pool, accessing the desktop source requiring maintenance, automatically transferring the desktop source requiring maintenance from a source pool to the temporary pool, determining that an issue with the desktop source transferred to the temporary pool is rectified and automatically transferring the desktop source from the temporary pool to the source pool when the issue is rectified. | 06-24-2010 |
Raghav Bhaskar, Bangalore IN
| Patent application number | Description | Published |
|---|---|---|
| 20110004607 | TECHNIQUES FOR REPRESENTING KEYWORDS IN AN ENCRYPTED SEARCH INDEX TO PREVENT HISTOGRAM-BASED ATTACKS - A method and system for cryptographically indexing, searching for, and retrieving documents is provided. In some embodiments, an encryption system is provided that generates a document index that allows users to retrieve documents by performing encrypted queries for keywords associated with the documents. In some embodiments, each keyword maps to the same number of encrypted document identifiers. In some embodiments, an extractor graph is employed to map an indication of each keyword to a number of buckets storing encrypted document identifiers. In some embodiments, an order-preserving encryption system is provided. The encryption system uses an ordered index that maps encrypted instances of ordered attribute values to documents that are associated with those values. The ordered index enables queries containing query operators that rely on order, such as less than (“<”) or greater than (“>”), to be successfully performed on encrypted attribute values. | 01-06-2011 |
Rao Bs Bhaskar, Bangalore IN
| Patent application number | Description | Published |
|---|---|---|
| 20080209571 | Device for Secure Access to Digital Media Contents, Virtual Multi-Interface Driver and System for Secure Access to Digital Media Contents - A device for secure access to digital media contents, the device comprising an access means for accessing digital media contents from a data source and a reader for authenticating a user, the authentication being performed by checking some authentication data. An internal communication path between the access means and the reader is not directly accessible from outside the device. | 08-28-2008 |
Tarun Bhaskar, Bangalore IN
| Patent application number | Description | Published |
|---|---|---|
| 20090177598 | METHOD FOR BUILDING PREDICTIVE MODELS WITH INCOMPLETE DATA - A method that imputes missing values while building a predictive model. A population of solutions is created using a data set comprising missing values, wherein each solution comprises parameters of each of the predictive models and the missing values of a data set. Each of the solutions in a population is checked for fitness. After the fitness is checked, the solutions in a population are genetically evolved to establish a successive population of solutions. The process of evolving and checking fitness is continued until a stopping criterion is reached. | 07-09-2009 |
| 20090177599 | SYSTEM AND METHOD FOR DEVELOPING A PROPENSITY MODEL - A technique is provided for developing a propensity model for customer behavior. Multiple biased samples of customer characteristics and results from past activities are established. Initial propensity models are created for each biased sample. The propensity models established for each biased sample are processed separately from the propensity models established for the other biased samples. A genetic algorithm is used to evolve the propensity models. A select number of propensity models that best fit their respective biased samples are compared to a validation sample that is unbiased. A select number of these propensity models that best fit the validation sample are cross-bred into the propensity models established for each biased sample. The propensity models for each biased sample are then processed again using the genetic algorithms. However, a number of elite propensity models are maintained in their original form and not evolved using the genetic algorithm. This cycle continues until a stopping criterion is reached. | 07-09-2009 |
| 20090177600 | SYSTEM AND METHOD FOR COARSE-CLASSING VARIABLES IN A PREDICTIVE MODEL - A technique is provided to coarse-class one or more customer characteristics used in a predictive model. A set of functions are used to represent partition points of the customer characteristic into smaller classes. Each of the final classes of the customer characteristic is represented separately in the predictive model. An initial set of functions may be established to provide an initial set of partitions points of the customer characteristic. The set of functions is then processed using a genetic algorithm to evolve the partition points to new values. Processing the set of partitions using the genetic algorithm may continue until a stopping criterion is reached. | 07-09-2009 |