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.

Data clustering using hybrid improved cuckoo search method

Abstract: Data clustering is one of the prominent fields of data mining which detects natural groups in a dataset. For the high dimensional dataset, traditional methods generally do not perform efficiently to cluster the data. Therefore, this paper proposes a novel metaheuristic method for data clustering based on k-means and improved cuckoo search to extend the capabilities of traditional clustering methods. The effectiveness of proposed method is tested on the three microarray datasets. Experimen­tal results validate that the proposed method outperforms the existing methods.

Blockchain Based Framework for Modeling and Evaluating 5G Spectrum Sharing

Abstract: The fifth-generation (5G) cellular technology aims at providing network services at high speed with reliable Quality of Service (QoS). To enable this, 5G deploys Massive Multi-Input Multi-Out-put (MIMO) to increase the capacity of a Base Station (BS) and the efficiency of the network. Provisioning guaranteed and reliable services to support MIMO requires effective resource management. Blockchain is a highly promising solution to enable multi-dimensional management of various resources such as spectrum allocation and user association. It can potentially mitigate spectrum under-utilization and can help in scaling up the deployment of different 5G services. In this article, we present a model for Blockchain-based multi-operator service provisioning for 5G users with Intra and Inter spectrum management among multiple telecom operators. In particular, we present a Blockchain-based implementation model for spectrum sharing between the operators to minimize spectrum under-utilization.

An Improvised Extractive Approach to Hindi Text Summarization

Abstract: Text summarization is defined as a task of minimizing a text that is produced from one or more texts such that the actual significant information in the texts is not lost. A text summarization tool compresses the text and displays only the important content to the user. Using text summarization, decisions can be made in lesser time and the core of the document be understood. This paper emphasizes on an extractive approach and its implementation on Java. The extractive approach selects the significant sentences based on a thematic approach. Before selecting the thematic words the Hindi stop-words was removed and also the stemming process to retrieve the root words in the sentences under consideration. Stop-word elimination eliminates the semantically null words from the input document and stemming helps in clustering together words with the same radix term. The system is based on an algorithm for scoring the sentences based on occurrence of the radix of thematic words. The sentences with highest score are added to the summary. The generated summary is further processed based on removal of extraneous phrases from the previously selected summary sentences so as to bring the sentences closer to human generated summary. The testing of the accuracy of the system can be made by using a technique called The Expert Game. In expert game, experts underline and extract the most interesting or informative fragments of the text. The recall and precision of the system’s summary is measured against the human’s extract. Based on the testing, the system is found to be 85 % accurate.

Generalized Intuitionistic Fuzzy Entropy Measure of Order α and Degree β and Its Applications to Multi-Criteria Decision Making Problem

Abstract: The objective of this manuscript is divided into two fold. Firstly, a more generalized intuitionistic fuzzy entropy measure of order and degree has been presented for measuring the degree of fuzziness of the set with a proof of its validity. A structured linguistic variable has been taken as an illustrative example to show its validity and superiority than the existing measures. Furthermore, based on this measure, an approach to deal with multi-criteria decision making MCDM problem is developed. Finally, a practical example is provided to illustrate the decision making process. A computed result is compared with the help of existing results. A sensitivity analysis on the different values of the parameters will make a decision maker more choice for accessing their results.