Database

Latest Innovations

A Method for Understanding Web Query Interfaces: Best-Effort Parsing with Hidden Syntax

 

 

A computer program product being embodied on a computer readable medium for extracting semantic information about a plurality of documents being accessible...

DNA-Based Data Storage Using Portable Sequencer

 

Dr. Milenkovic has developed a new method for error-free random access data storage through DNA that uses a portable nanopore sequencer. The error correction methods used...

Native DNA Based Storage and Computing via Single Strand Nicking

Prof. Milenkovic from the University of Illinois at Urbana-Champaign has developed a new method for DNA based storage of information. In...

Solid-State Drive

The University of Illinois’ TimeSSD and TimeKits tools are a firmware-level augmentation to solid state drive (SSD) architecture. The technology uses intrinsic...

SemiSynBio: An On-Chip Nanoscale Storage System Using Chimeric DNA

Dr. Milenkovic from the University of Illinois has developed an on-chip integrated nanosytem for writing, storage, access, and reading of large data volumes that utilizes...

Image Processing and Error-Correction in DNA via Inpainting and Filtering

Dr. Olgica Milenkovic and Dr. Charles Schroeder at the University of Illinois has developed an error-correction method for DNA-based data storage of massive image datasets.  Previous methods for...

Dr. Olgica Milenkovic and Dr. Charles Schroeder at the University of Illinois has developed an error-correction method for DNA-based data storage of massive image datasets.  Previous methods for addressing errors use Reed-Solomon codes at both the individual oligo and pool of oligo level to reconstruct missing strings from redundantly encoded oligos. 

This method uses deep learning techniques to utilize natural redundancy present in the images to perform inpainting on the missing pixels, reconstructing the missing information, and avoiding the requirement for synthesizing and sequencing redundancy in the oligos.