J
J. K. Das
Researcher at KIIT University
Publications - 45
Citations - 187
J. K. Das is an academic researcher from KIIT University. The author has contributed to research in topics: Computer science & Memristor. The author has an hindex of 6, co-authored 41 publications receiving 113 citations.
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Journal ArticleDOI
An integrated approach for identification of exon locations using recursive Gauss Newton tuned adaptive Kaiser window.
TL;DR: This work proposes a robust approach combining the Trigonometric mapping with Adaptive tuned Kaiser Windowing approach for locating the protein coding regions (EXONS) in a genetic sequence and reveals efficient prediction of exon location in contrast to the other existing mapping methods.
Journal ArticleDOI
Future Wireless Communication Technology towards 6G IoT: An Application-Based Analysis of IoT in Real-Time Location Monitoring of Employees Inside Underground Mines by Using BLE
Sushant Kumar Pattnaik,Soumya Ranjan Samal,Shuvabrata Bandopadhaya,Kaliprasanna Swain,Subhashree Choudhury,J. K. Das,Albena Mihovska,Vladimir Poulkov +7 more
TL;DR: An IoT-based real-time location monitoring system using Bluetooth Low Energy (BLE) for underground communication applications and an application-based analysis of industrial positioning systems are presented.
Proceedings ArticleDOI
Odia Braille: Text transcription via image processing
TL;DR: For this, image processing using MATLAB technique provides a suitable platform to perform the segmentation of Braille cell for pattern selection and hence, Odia letter and word recognition in Braille code representing Odia language into Odia word as text.
Proceedings ArticleDOI
Design and stability analysis of CNTFET based SRAM Cell
TL;DR: In this article, the authors compared the performance of the conventional 6T SRAM cell with the Carbon Nanotube Field Effect Transistors (CNTFET) based SRAM cells.
Proceedings ArticleDOI
Advanced protein coding region prediction applying robust SVD algorithm
TL;DR: A variation of the Singular Value Decomposition (SVD) algorithm based on the pseudo EIIP mapping for exon location detection is presented, using spectral peaks at 1/3 frequency component position of DNA sequence to identify the exons location.