Jaypee Institute of Information Technology

About: Jaypee Institute of Information Technology is a education organization based out in Noida, Uttar Pradesh, India. It is known for research contribution in the topics: Computer science & Cluster analysis. The organization has 2136 authors who have published 3435 publications receiving 31458 citations. The organization is also known as: JIIT Noida.

Orthogonal-state-based and semi-quantum protocols for quantum private comparison in noisy environment

Abstract: Private comparison is a primitive for many cryptographic tasks, and recently several schemes for the quantum private comparison (QPC) have been proposed, where two users can compare the equality of their secrets with the help of a semi-honest third party (TP) without knowing each other's secret and without disclosing the same to the TP. In the exisiting schemes, secrecy is obtained by using conjugate coding, and considering all participants as quantum users who can perform measurement(s) and/or create states in basis other than computational basis. In contrast, here we propose two new protocols for QPC, first of which does not use conjugate coding (uses orthogonal states only) and the second one allows the users other than TP to be classical whose activities are restricted to either reflecting a quantum state or measuring it in computational basis. Further, the performance of the protocols is evaluated under various noise models.

Children's influence in family buying process in India

Abstract: Purpose – The purpose of this paper is twofold: to categorize and rank products based on children's influence and to compare their influence on the different stages of the family buying process.Design/methodology/approach – The study was based on an extensive literature review and focus group discussions. Using a structured questionnaire, a survey was conducted with children aged 8‐12 years. The sample size was 175.Findings – Factor analysis revealed three distinct product clusters: “loud”, “noisy” and “quiet” goods. Children's influence was found to be highest for noisy goods, lesser for loud goods and lowest for quiet goods. One‐way MANOVA analysis found that for loud and noisy goods children's influence was highest in the initiation stage, and lowest in the search stage. For quiet goods, the highest influence was in the final decision stage followed by initiation and choice stage.Practical implications – The identified product clusters and children's relative influence across the buying stages for thes...

Traffic Jam Probability Estimation Based on Blockchain and Deep Neural Networks

Abstract: The exponential surge in the number of vehicles on the road has aggravated the traffic congestion problem across the globe. Several attempts have been made over the years to predict the traffic scenario accurately and consequently avoiding further congestion. Crowdsourcing has come forward as one of the most adopted methods for predicting traffic intensity using live data. However, the privacy concerns and the lack of motivation for the live users to help in the traffic prediction process have rendered existing crowdsourcing models inefficient. Towards this end, we present an advanced blockchain-based secure crowdsourcing model. Not only does our model ensure privacy preservation of the users, but by incorporating a revenue model, it also provides them with an incentive to participate in the traffic prediction process willingly. For accurate and efficient traffic jam probability estimation, our work proposes a neural network-based smart contract to be deployed onto the blockchain network. The results reveal that the proposed model is highly efficient in terms of attaining high participation and consequently obtaining highly accurate predictions.