Savita Kumari Sheoran

@igu.ac.in

Professor, Department of Computer Science & Engineering, Faculty of Engineering and Technology
Indira Gandhi University Meerpur, Reewari



              

https://researchid.co/savita.sheoran

EDUCATION

MCA, Ph.D.

RESEARCH INTERESTS

Computer Science & Engineering

4

Scopus Publications

156

Scholar Citations

7

Scholar h-index

6

Scholar i10-index

Scopus Publications

  • Modified ARIMA Model for Improving Certainty in Spatio-Temporal Crime Event Prediction
    Romika Yadav and Savita Kumari Sheoran
    IEEE
    Crimes are serious threat to society. The recent economic developments and globalizations have bloated it as serious global concern associated with demographic factors due to which crime site selection and pattern identification have became a central concern in crime prediction. During spatio-temporal crime prediction Linear Model and Generalized Linear Model are used for quantitative improvement in prediction. Both of these models lack certainty in crime prediction. In this paper we have enhanced the Generalized Linear Model for Crime Site Selection and analyze it for crime events using Modified ARIMA (Auto Regressive Integrated Moving Average) with big data technologies. Such enhancement is support similar crime trends among various crime locations for criminal site selection. The simulation results show that out model presents a more significant insight into the scope and complexion of crime prediction and improves certainty in crime prediction.

  • Crime Prediction Using Auto Regression Techniques for Time Series Data
    Romika Yadav and Savita Kumari Sheoran
    IEEE
    Crime is undesired anti-social behavior and poses serious threat to society. The civilized societies make everything possible to reduce crime within its regime of influence. Alarming the crime prone areas in advance is one of the best strategies for crime to be ceased to happen. The recent socio-economic developments and proliferation of internet technologies have turned the crime into a global phenomenon. In such scenario the crime data to be dealt is huge in volume, diverse in variety and highly location dependent. Hence the contemporary crime data set is highly spatio-temporal in nature where the traditional system of criminal records has failed to maintain the desired level of intelligence and make a substantial prediction. A blend of ‘Big data’ tools for data management and Generalized Linear Regression for statistical analysis is used to draw a useable inference from such time series data set. Such enhancement is supportive to detect similar crime trends among various crime locations for criminal site selection. Consequently ARIMA (Auto Regressive Integrated Moving Average) model affords to minimize the error generated in the predictive model. This research paper aims to locate the offender site in advance with more accuracy. We have explored the Auto Regression Techniques to accurately predict the crime with minimum error for such time series data by identifying the relationship among crimes attributes. The experimental result obtained using "R" tool show that our formulation work well for all parameters and improves certainty in prediction.

  • Dual segment video watermarking using energy efficient technique
    Jeebananda Panda, Indu Kumari, Nitish Goel, and Savita Kumari
    IEEE
    Digital watermarking is a technique to employ copyright protection and ensure the authenticity of the owner using a proof of ownership embedded in a multimedia file. The objective of this paper is to present a novel digital video watermarking scheme using dual watermark. The binary watermark image is distributed over audio samples in which first four samples of each frame are watermarked with 4 bits of the image using multiple bit plane scheme. For the gray scale watermark, the FFT is taken and the samples are embedded in the FFT samples of video frames using Energy Efficient scheme. The watermarked video is subjected to different attacks and the efficiency of the technique is measured using Correlation Factor and PSNR. The algorithm presented is robust, secure and is energy efficient with decreased payload on the host signal.

  • Data broadcast management in wireless communication: An emerging research area
    Seema Verma, Rakhee Kulshrestha, and Savita Kumari
    IGI Global
    The data broadcast policies have been developed for single channel and multi channel with various scheduling and indexing techniques. For the data management policies which consider the different broadcast cycles for different broadcast operators, it can be said that traditional types of data management policies are known previously, and the policies of Central Server (CS) and Unified Index Hub (UIH), which consider single broadcast cycle for all operators, are recent. This chapter presents both strategies very simply for better understanding, discusses the work done in the past and present on data broadcast management, along with suggestions for the future possibilities to explore the field.

RECENT SCHOLAR PUBLICATIONS

  • Leaf Diseases Detection in Peach Using EfficientNet
    DG Singh
    Communications in Computer and Information Science, International Conference 2024

  • Fidelity and Accuracy trade-off in quantum kernels
    RS Seema Verma, Savita Sheoran
    International Journal of Physics and Applications 2024

  • The role of Deep Learning in Attaining the Sustainable Development Goals
    N Yadav, S kumari Sheoran
    2024 First International Conference on Technological Innovations and Advance 2024

  • Fidelity and Accuracy trade-off in quantum kernels
    S Verma, SK Sheoran, RK Sheoran
    interaction 3, 4 2024

  • Topological quantum error correction with semions
    S Verma, SK Sheoran, RK Sheoran
     2024

  • Comparative Analysis of Classification Efficiency of Quantum Machine Learning Algorithms
    SK Sheoran, V Yadav
    2024 IEEE International Conference on Computing, Power and Communication 2024

  • Analysis of Machine Learning Techniques for Knob Tuning
    S Sheoran, Deepak
    2024 IEEE International Conference on Computing, Power and Communication 2024

  • Quantum Computing Research: Ontological Study of the Quantum Computing Research Ecosystem
    RK Sheoran, S Verma, SK Sheoran, V Yadav
    Applications and Principles of Quantum Computing, 236-263 2024

  • Exploring the Confluence: Trends, Challenges, and Future Trajectories in IoT and WoT from 2018 to 2023
    SR sheoran, savita
    International Conference on Recent Trend in Science Engineering and 2023

  • Promises and Perils of Post-Quantum Blockchain
    SK Sheoran, G Yadav
     2023

  • Exploring the Confluence: Trends, Challenges, and Future Trajectories in IoT and WoT from 2018 to 2023
    SK Sheoran, S Ranga
     2023

  • Big data for address security and privacy issues in social networks
    SK Sheoran, R Yadav
    International Conference on Latest Trends in Science, Engineering and 2023

  • GeoWebCln: An Intensive Cleaning Architecture for Geospatial Metadata
    SK Sheoran, V Parmar
    Quaestiones Geographicae 41 (1), 51-62 2022

  • A SCIENTOMETRIC STUDY OF RESEARCH TRENDS IN BLOCKCHAIN
    SK Sheoran, RK Sheoram
    ICRETM 2022

  • Research Hotspots in Quantum Error Correction using Artificial Intelligence Techniques
    RKS Prof. (Dr.) Seema Verma, Prof. (Dr.) Savita Kumari Sheoran
     2022

  • An Extended Work Architecture for Online Threat Prediction in Tweeter Dataset
    SK Sheoran, P Yadav
    International Journal of Computer Science & Network Security 21 (1), 97-106 2021

  • Machine Learning based Optimization Scheme for Detection of Spam and Malware Propagation in Twitter
    SK Sheoran, P Yadav
    Machine Learning 12 (2) 2021

  • Context-based spatial metadata cleaning using QGIS
    V Parmar, S Sheoran
    Vidyabharati International Interdisciplinary Research Journal 12 (1), 55-62 2021

  • Identification of alternative landfill site using QGIS in a densely populated metropolitan area
    SK Sheoran, V Parmar
    Quaestiones Geographicae 39 (3), 47–56-47–56 2020

  • Visual Analysis of Spatial Metadata
    SK Sheoran, V Parmar
    International Journal of Computer Theory and Engineering 12 (4), 102-105 2020

MOST CITED SCHOLAR PUBLICATIONS

  • Challenges in Developing Citizen-Centric E-Governance in Libya.
    S Verma, S Kumari, M Arteimi, A Deiri, R Kumar
    Int. Arab. J. e Technol. 2 (3), 152-160 2012
    Citations: 26

  • Crime prediction using auto regression techniques for time series data
    R Yadav, SK Sheoran
    2018 3rd international conference and workshops on recent advances and 2018
    Citations: 25

  • Impact of big data and social media on society
    S Kumari
    Global Journal for Research Analysis 5, 437-438 2016
    Citations: 15

  • BREAST CANCER CLASSIFICATION USING BIG DATA APPROACH
    savita kumari sheoran
    Indian Journal of research 7 (01), 401-403 2018
    Citations: 14

  • Modified ARIMA model for improving certainty in spatio-temporal crime event prediction
    R Yadav, SK Sheoran
    2018 3rd International Conference and Workshops on Recent Advances and 2018
    Citations: 11

  • Big data: A big boon for tourism sector
    SK Sheoran
    International Journal of Research in Advanced Engineering and Technology 3 2017
    Citations: 11

  • Applied Signal and Image Processing: Multidisciplinary Advancements
    R Qahwaji, R Qahwaji, R Green, EL Hines
    IGI Global 2011
    Citations: 8

  • GeoWebCln: An Intensive Cleaning Architecture for Geospatial Metadata
    SK Sheoran, V Parmar
    Quaestiones Geographicae 41 (1), 51-62 2022
    Citations: 6

  • Autoregressive model for multivariate crime prediction
    R Yadav, SK Sheoran
    Decision Analytics Applications in Industry, 301-307 2020
    Citations: 5

  • Identification of alternative landfill site using QGIS in a densely populated metropolitan area
    SK Sheoran, V Parmar
    Quaestiones Geographicae 39 (3), 47–56-47–56 2020
    Citations: 4

  • Analysis of criminal behavior through clustering approach
    R Yadav, SK Savita
    Int. J. Comput. Sci. Eng 6 2018
    Citations: 3

  • Make in India campaign and India’s IT-BPM sector
    SK Sheoran
    International Journal of Applied Research 3 (1), 471-475 2017
    Citations: 3

  • Dual segment video watermarking using energy efficient technique
    J Panda, I Kumari, N Goel, S Kumari
    2016 1st India International Conference on Information Processing (IICIP), 1-6 2016
    Citations: 3

  • Big Data and social Media to improve the Quality of Higher education
    S Kumari
    IJCSMC 5 (3), 179-185 2016
    Citations: 3

  • Comparative Analysis of Classification Efficiency of Quantum Machine Learning Algorithms
    SK Sheoran, V Yadav
    2024 IEEE International Conference on Computing, Power and Communication 2024
    Citations: 2

  • Machine Learning based Optimization Scheme for Detection of Spam and Malware Propagation in Twitter
    SK Sheoran, P Yadav
    Machine Learning 12 (2) 2021
    Citations: 2

  • Threats Detection using Big Data Analytics
    SK Sheoran, P Yadav
    International Journal of Advanced Research in Computer Science 8 (1) 2017
    Citations: 2

  • Computational model for Spatio temporal crime event prediction
    SK Sheoran, R Yadav
    International Journal of Advanced Research in Computer Science 8 (1) 2017
    Citations: 2

  • Social Media Applications for Disaster Management
    S Kumari
    International Journal of Science and Research (IJSR) 5 (3), 1358-1361 2016
    Citations: 2

  • Exploring Classical Security Techniques for Cloud Computing Environment
    S Kumari
    International Journal of Computer Application 4 (4), 86-94 2014
    Citations: 2