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.

On Generalized Exponential Fuzzy Entropy

Abstract: —In the present communication, the existing measures offuzzy entropy are reviewed. A generalized parametric exponentialfuzzy entropy is defined.Our study of the four essential and someother properties of the proposed measure, clearly establishes thevalidity of the measure as an entropy. Keywords —fuzzy sets, fuzzy entropy, exponential entropy, expo-nential fuzzy entropy. I. I NTRODUCTION The notion of fuzzy sets was proposed by Zadeh [13] in1965 with a view to tackling problems in which indefinitenessarising from a sort of intrinsic ambiguity plays a fundamentalrole. Fuzziness, a feature of uncertainty, results from the lackof sharp distinction of the boundary of a set, i.e., an individualis neither definitely a member of the set nor definitely nota member of it. The first attempt to quantify the fuzzinesswas made in 1968 by Zadeh [14], who based on probabilisticframework introduced the entropy combining probability andmembership function of a fuzzy event as weighted Shannonentropy [11]. De Luca and Termini [2] formulated axiomswith which the fuzzy entropy measure should comply anddefined a kind of entropy of a fuzzy set based on Shannon’sfunction. Yager [12] defined an entropy measure of a fuzzyset in terms of a lack of distinction between fuzzy set andits negation based on norm. Pal and Pal [8, 9] proposed anentropy based on exponential function to measure the fuzzinesscalled exponential fuzzy entropy. Hwang and Yang [4] definedfuzzy entropy by combining the concepts of Yager [12] andPal and Pal [8, 9]. Some parametric generalizations of DeLuca and Termini’s entropy [2] have been studied by Kapur[7], Hooda [5], Bhandari and Pal [1], Fan and Ma [3].Theseparameters give certain flexibility in applications and theirvalues have ultimately to be determined from the data itself.In this paper, new parametric generalized exponential entropyis proposed. This paper is organized as follows: In Section2 some basic definitions related to probability and fuzzyset theory are briefly discussed. In Section 3 a new fuzzyentropy measure called,

Research on optimization of scientific research performance management based on BP neural network

Abstract: Higher education in my country needs to focus on the cultivation of innovative talents, independent innovation, technological development, cultural innovation, and the promotion of scientific and technological knowledge. This paper proposes a performance index system for university social science research based on BP neural network and the relevant theoretical knowledge is utilized to construct a university social science research performance evaluation model. The results show that the difference between the predicted value of each sample and its expected output value is not large, and the value of the prediction error is also relatively small, all less than 1. In this paper, the performance evaluation method of social science research in colleges and universities based on BP neural network is an evaluation method with high efficiency, strong operability and high accuracy. Therefore, the BP neural network model is utilized to evaluate and optimize the performance of social science research in colleges and universities. The established BP neural network model has very low error value and good generalization ability, which effectively proves that the training sample data can fit the neural network simulation ideally. In the same way, it shows that the output value of BP neural network can be very close to the input vector.

Non-intrusive speech quality assessment using several combinations of auditory features

Abstract: Quality estimation of speech is essential for monitoring and maintenance of the quality of service at different nodes of modern telecommunication networks. It is also required in the selection of codecs in speech communication systems. There is no requirement of the original clean speech signal as a reference in non-intrusive speech quality evaluation, and thus it is of importance in evaluating the quality of speech at any node of the communication network. In this paper, non-intrusive speech quality assessment of narrowband speech is done by Gaussian Mixture Model (GMM) training using several combinations of auditory perception and speech production features, which include principal components of Lyon's auditory model features, MFCC, LSF and their first and second differences. Results are obtained and compared for several combinations of auditory features for three sets of databases. The results are also compared with ITU-T Recommendation P.563 for non-intrusive speech quality assessment. It is found that many combinations of these feature sets outperform the ITU-T P.563 Recommendation under the test conditions.

A mobile data offloading framework based on a combination of blockchain and virtual voting

Abstract: The emergence of mobile cloud computing enables mobile users to offload computation tasks to other resource‐rich mobile devices to reduce energy consumption and enhance performance. A direct peer‐to‐peer connection among mobile devices to offload computation tasks can be a highly promising solution to provide a fast mechanism, especially for deadline‐sensitive offloading tasks. The generic blockchain‐based system might fail in such a scenario due to it being a heavyweight mechanism requiring high power consumption in the mining process. To address these issues, in this article, we propose a directed acyclic graph‐enabled mobile offloading (DAGMO) algorithm. DAGMO model is empowered by traditional blockchain features and provides additional advantages to overcome the fundamental limitations of generic blockchain. A game‐theoretic approach is used to model the interactions between mobile devices. The numerical analysis proves the proposed model to enhance the overall welfare of the participating nodes in terms of computation cost and time.