Indian Institute of Technology, Jodhpur

About: Indian Institute of Technology, Jodhpur is a education organization based out in Jodhpur, India. It is known for research contribution in the topics: Computer science & Welding. The organization has 914 authors who have published 2221 publications receiving 19243 citations.

Magnetic Nanoparticles to Unique DNA Tracers: Effect of Functionalization on Physico-chemical Properties.

Abstract: To monitor and manage hydrological systems such as brooks, streams, rivers, the use of tracers is a well-established process. Limited number of potential tracers such as salts, isotopes and dyes, make study of hydrological processes a challenge. Traditional tracers find limited use due to lack of multiplexed, multipoint tracing and background noise, among others. In this regard, DNA based tracers possess remarkable advantages including, environmentally friendly, stability, and high sensitivity in addition to showing great potential in the synthesis of ideally unlimited number of unique tracers capable of multipoint tracing. To prevent unintentional losses in the environment during application and easy recovery for analysis, we hereby report DNA encapsulation in silica containing magnetic cores (iron oxide) of two different shapes—spheres and cubes. The iron oxide nanoparticles having size range 10–20 nm, have been synthesized using co-precipitation of iron salts or thermal decomposition of iron oleate precursor in the presence of oleic acid or sodium oleate. Physico-chemical properties such as size, zeta potential, magnetism etc. of the iron oxide nanoparticles have been optimized using different ligands for effective binding of dsDNA, followed by silanization. We report for the first time the effect of surface coating on the magnetic properties of the iron oxide nanoparticles at each stage of functionalization, culminating in silica shells. Efficiency of encapsulation of three different dsDNA molecules has been studied using quantitative polymerase chain reaction (qPCR). Our results show that our DNA based magnetic tracers are excellent candidates for hydrological monitoring with easy recoverability and high signal amplification.

A novel feature transform framework using deep neural network for multimodal floor plan retrieval

Abstract: In recent past, there has been a steep increase in the use of online platforms for the search of desired products. Real estate industry is no exception and has started initiating rent/sale of houses through online platforms. In this paper, we propose a deep neural network framework to facilitate automatic search of homes based on their floor plans. The salient features of this framework are that the query can be either an image (existing floor plan) or a sketch through a sketch pad interface. Our proposed framework automatically determines the type of query (image or sketch) and retrieves similar floor plan images from the database. The critical contributions of our proposed approach are: (1) a novel unified floor plan retrieval framework using multimodal query, i.e., an intuitive and convenient sketch query mode as well as a query by example mode ; (2) a conjunction of autoencoder, Cyclic GAN and CNN for the task of domain mapping and floor plan image retrieval. We have reported results of extensive experimentation and comparison with baseline results to establish the effectiveness of our approach.