| INDIAN STATISTICAL INSTITUTE Patent applications |
| Patent application number | Title | Published |
|---|
| 20130115703 | DILUTION METHOD FOR DIGITAL MICROFLUIDIC BIOCHIPS - Systems and methods are provided for producing fluids with desired concentration factors. According to one embodiment, a sequence of mix steps comprises mixing a resultant solution of a preceding mix step with one of the input solutions of the preceding mix step depending on a concentration factor of the resultant solution. If the concentration factor of the resultant solution is higher than the target concentration factor, then the resultant solution is mixed with the input solution having the lower concentration factor. If the concentration factor of the resultant solution is lower than the target concentration factor, then the resultant solution is mixed with the input solution having the higher concentration factor. | 05-09-2013 |
| 20120254163 | DETERMINING A RELATIVE IMPORTANCE AMONG ORDERED LISTS - Implementations and techniques for determining a relative importance among ordered lists are generally discussed. | 10-04-2012 |
| 20120183225 | ROUGH WAVELET GRANULAR SPACE AND CLASSIFICATION OF MULTISPECTRAL REMOTE SENSING IMAGE - Shift-invariant wavelet transform with properly selected wavelet base and decomposition level(s), is used to characterize rough-wavelet granules producing wavelet granulation of a feature space for a multispectral image such as a remote sensing image. Through the use of the granulated feature space contextual information in time and/or frequency domains are analyzed individually or in combination. Neighborhood rough sets (NRS) are employed in the selection of a subset of granulated features that further explore the local and/or contextual information from neighbor granules. | 07-19-2012 |
| 20120123980 | OPTIMIZATION TECHNIQUE USING EVOLUTIONARY ALGORITHMS - Provided embodiments include a method, a system, a device, and an article of manufacture. A system for terminating a genetic algorithm (GA), where the GA uses an iterator and generates one best solution per iteration, includes a memory, an iterative processor, and a terminating processor. The memory is provided for storing a plurality of best solutions generated in a plurality of iterations of the GA. One of the best solutions generated in one of the iterations is stored in the memory if the one of the best solutions is better than a previous one of the best solutions generated in a previous one of the iterations. The iterative processor computes a variance of the plurality of the best solutions stored in the memory. The terminating processor terminates the iterator when the variance is less than or equal to a predetermined threshold. | 05-17-2012 |
| 20110246409 | DATA SET DIMENSIONALITY REDUCTION PROCESSES AND MACHINES - Provided in part herein are processes and machines that can be used to reduce a large amount of information into meaningful data and reduce the dimensionality of a data set. Such processes and machines can, for example, reduce dimensionality by eliminating redundant data, irrelevant data or noisy data. Processes and machines described herein are applicable to data in biotechnology and other fields. | 10-06-2011 |
