Institution
Narula Institute of Technology
About: Narula Institute of Technology is a based out in . It is known for research contribution in the topics: Quantum dot cellular automaton & Cognitive radio. The organization has 288 authors who have published 490 publications receiving 2258 citations. The organization is also known as: NiT.
Topics: Quantum dot cellular automaton, Cognitive radio, Genetic algorithm, Wireless sensor network, Computer science
Papers published on a yearly basis
Papers
More filters
••
22 Jun 2013TL;DR: An Artificial Neural Network based approach for implementing Automatic Signature verification and authentication system that has been compared with some existing system and it has been observed that this system shows better performance.
Abstract: This paper proposes an Artificial Neural Network based approach for implementing Automatic Signature verification and authentication system. In this era, with the rapid growth of Internet and the necessity of localized verification systems, handwritten signature has become an important biometric feature for the purpose of verification and authentication. The proposed method comprises spatial and frequency domain techniques for transformation. After extracting the Region of Interest Ripplet-II Transformation, Fractal Dimension and Log Polar Transformation are carried out to extract descriptors of the concerned signature to be verified as well as authenticated. In decision making stage Feed Forward Back Propagation Neural Network is used for verification and authentication purpose. This system has been tested with large sample of signatures to show its verification accuracy and the results have been found around 96.15%. Also forgery detection rate has been found 92% which is very encouraging. False Acceptance Rate and False Rejection rate of our system has been determined 5.28% and 2.56% respectively. This approach has been compared with some existing system and it has been observed that this system shows better performance.
8 citations
••
30 Jun 2011TL;DR: This work has considered a cognitive radio network in which there is a single cell and a Base Station within that cell and Genetic Algorithm (GA) has been used to solve the allocation problem.
Abstract: We have considered a cognitive radio network in which there is a single cell and a Base Station (BS) within that cell. Our objective is to maximize the channel allocation of the active subscribers within that network. Genetic Algorithm (GA) has been used to solve the allocation problem. Power control has not been considered here. Our approach channel allocation using GA (CAGA) yields better result with respect to percentage of customer premise equipment (CPEs) covered than previously reported Dynamic Interference Graph (DIGA) allocation and Minimum Incremental power allocation method (MIPA).
8 citations
••
25 Oct 2020TL;DR: In this article, the authors analyze the clashes between the two and the potential solutions to those clashes for blockchain to comply with GDPR, which clashes with the blockchain's decentralized data storage and management process.
Abstract: Data Governance is the trending topic in today’s security-privacy-concerned digital ecosystem. Blockchain technology is probably one of the most acclaimed evolutions in recent times. Blockchain technologies can be a game-changer for data governance in the areas of transparency and data provenance. As a distributed ledger technology (DLT), blockchain is being touted as a potentially transformational force in collaborative data governance. The General Data Protection Regulation (GDPR) entered into force on May 25, 2018. It is the latest in a series of European Union (EU) legislative measures designed to give EU citizens more control over their data. GDPR, which directs a centralized ‘data controller’ (GDPR Article 4) to manage user data, clashes with the blockchain’s decentralized data storage and management process. The GDPR and the blockchain both have a common ideological ground, emphasizing the need for a change in managing personal data. While GDPR takes care of the policy side by setting up a standard, the blockchain helps enable the implementation side by providing a unique framework. In this paper, the authors analyze the clashes between the two and the potential solutions to those clashes for blockchain to comply with GDPR.
8 citations
••
TL;DR: In this paper, the authors presented theoretical and experimental investigation of a novel, reduced size Microstrip Frequency Selective Surface (MSSS), which is achieved by cutting some rectangular slots at four sides of a square patch.
Abstract: The study presents theoretical and experimental investigation of a novel, reduced size Microstrip Frequency Selective Surface The novel design is achieved by cutting some rectangular slots at four sides of a square patch Compared with conventional square patch Frequency Selective Surface (FSS), this slotted square patch Microstrip FSS can achieve reduction in patch area of 36% The structure acts like a band pass filter with a resonant frequency 8 GHz Both theoretical and experimental investigations are done Theoretical investigation is done by IE3D software Experimental investigation is performed using standard microwave test bench © 2007 Wiley Periodicals, Inc Microwave Opt Technol Lett 49: 2820–2821, 2007; Published online in Wiley InterScience (wwwintersciencewileycom) DOI 101002/mop22833
8 citations
••
TL;DR: The applicability of Ritz-variational principle for 3dnf ((1,3)D(o)) states lying between N=2 and N=3 ionization threshold of singly ionized helium is discussed in this communication.
Abstract: The applicability of Ritz-variational principle for 3dnf (D1,3o) states lying between N=2 and N=3 ionization threshold of singly ionized helium is discussed in this communication. Probable existence of such a state for O6+ within the planetary atmosphere in the polar regions of Jupiter is discussed.
8 citations
Authors
Showing all 288 results
Name | H-index | Papers | Citations |
---|---|---|---|
Kaushik Roy | 23 | 180 | 1579 |
Kunal Das | 18 | 78 | 1213 |
Tapan K. Mukherjee | 14 | 60 | 654 |
Jayanta K. Saha | 13 | 82 | 592 |
Avishek Chakraborty | 12 | 29 | 408 |
Abhijit Chakrabarti | 12 | 66 | 530 |
Mukul K. Das | 10 | 76 | 295 |
Zeenat Rehena | 9 | 26 | 235 |
Arijit Das | 9 | 73 | 329 |
Biswajit Halder | 8 | 20 | 156 |
Abhijit Ghosh | 8 | 22 | 335 |
Sumit Chabri | 8 | 23 | 284 |
Saradindu Panda | 7 | 51 | 142 |
Bikash Panja | 7 | 12 | 90 |
Sangita Roy | 7 | 26 | 170 |