Savita Kumari Sheoran

@igu.ac.in

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

Savita Kumari Sheoran


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https://researchid.co/savita.sheoran

EDUCATION

MCA, Ph.D.

RESEARCH INTERESTS

Computer Science & Engineering
4

Scopus Publications

190

Scholar Citations

8

Scholar h-index

6

Scholar i10-index

Scopus Publications

  • Modified ARIMA Model for Improving Certainty in Spatio-Temporal Crime Event Prediction
    Romika Yadav, Savita Kumari Sheoran
    3rd International Conference and Workshops on Recent Advances and Innovations in Engineering Icraie 2018, 2018
    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, Savita Kumari Sheoran
    3rd International Conference and Workshops on Recent Advances and Innovations in Engineering Icraie 2018, 2018
    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, Savita Kumari
    India International Conference on Information Processing Iicip 2016 Proceedings, 2017
    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, Savita Kumari
    Applied Signal and Image Processing Multidisciplinary Advancements, 2011
    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

  • Enhancing weed detection in wheat with hybrid attention mechanism CBAM: a comparative study with deep learning approaches
    Ritika, SK Sheoran, A Singh, D Kumar
    Frontiers in Agronomy 8, 1706873 , 2026
    2026
  • AI Future in Sustainable Soil Conservation: Challenges and Opportunities
    AK Pradhan, Ritika, D Kumar, SK Sheoran, MK Mishra, MK Singh
    Advancements in Soil Conservation: From Traditional Practices to AI-Driven … , 2026
    2026
  • A hybrid QSVM-QNN approach for breast cancer diagnosis using quantum feature maps
    RKS Vikesh Yadav​, Savita Kumari Sheoran
    PeerJ Computer Science , 2026
    2026
  • Robust evaluation of classical and quantum machine learning under noise, imbalance, feature reduction and explainability
    SK Sheoran, V Yadav, RK Sheoran
    Scientific Reports , 2025
    2025
    Citations: 3
  • Comparative Analysis of State-of-the-Art Deepfake Detection Models
    N Yadav, S Sheoran, I Sharma, D Dhindhwal
    2025 3rd International Conference on Advances in Computation, Communication … , 2025
    2025
  • AI-Based Image Forgery Detection (AI-IFD)
    N Yadav, S Sheoran
    2025 12th International Conference on Reliability, Infocom Technologies and … , 2025
    2025
  • Hybrid Evolutionary Bayesian Optimization for Cloud Database Knob Tuning
    S Sheoran
    2025 12th International Conference on Reliability, Infocom Technologies and … , 2025
    2025
  • Quantum Computing for Sustainable Energy: Optimising SDG-7 Through Smart Energy Management and Financial Planning
    SK Sheoran, V Yadav, RK Sheoran
    2025 International Conference on Modern Sustainable Systems (CMSS), 1012-1020 , 2025
    2025
  • Quantum k-Nearest Neighbour Classifier: Investigating Hybrid Feature map approach in Quantum Machine Learning utilizing Pennylane
    SK Sheoran, V Yadav, RK Sheoran
    2025 International Conference on Computing Technologies (ICOCT), 1-5 , 2025
    2025
    Citations: 1
  • Current Progress of Sustainable Smart Agriculture Using Internet of Things
    SK Sheoran, S Ranga, G Singh
    Emerging Smart Agricultural Practices Using Artificial Intelligence, 329-351 , 2025
    2025
  • Deep Fake Detection Using Hybrid CNN and Machine Learning Techniques
    N Yadav, SK Sheoran
    2025 International Conference on Networks and Cryptology (NETCRYPT), 801-805 , 2025
    2025
    Citations: 1
  • Exploring Quantum Neural Networks: A Multi-Platform Study on Quantum-Based Classification
    SK Sheoran, V Yadav, RK Sheoran
    2025 International Conference on Networks and Cryptology (NETCRYPT), 1286-1290 , 2025
    2025
  • Analysis of Quantum SVM and KNN on Azure Quantum
    SK Sheoran, V Yadav, RK Sheoran
    2025 5th International Conference on Pervasive Computing and Social … , 2025
    2025
  • Enhancing Data Classification with Hybrid QNNs and Quantum Feature Maps in Google Cirq
    SK Sheoran, V Yadav, RK Sheoran
    2025 Seventh International Conference on Computational Intelligence … , 2025
    2025
    Citations: 3
  • Detecting Leaf Disease and Classifying Images via Transfer Learning with VGG 16
    SK Sheoran
    2025 3rd International Conference on Disruptive Technologies (ICDT), 244-249 , 2025
    2025
  • EfficientNetB4 to EfficientNetB7 for Pepper Bell Plant Leaf Disease Detection: A Comparative Study
    S Ranga, SK Sheoran, G Singh, M Yadav
    2025 International Conference on Cognitive Computing in Engineering … , 2025
    2025
    Citations: 1
  • Synthetic Realities: A Critical Review of Deepfake Techniques
    M Yadav, SK Sheoran, G Singh
    2025 International Conference on Cognitive Computing in Engineering … , 2025
    2025
  • Digital Twins for the Agriculture Sector
    R Sheoran, Savita
    Blockchain and Digital Twin Applications in Smart Agriculture, 237-250 , 2025
    2025
    Citations: 1
  • Leaf Diseases Detection in Peach Using EfficientNet
    DG Singh
    Communications in Computer and Information Science, International Conference … , 2024
    2024
  • The role of deep learning in attaining the sustainable development goals
    N Yadav, SK Sheoran
    2024 First International Conference on Technological Innovations and Advance … , 2024
    2024
    Citations: 4

MOST CITED SCHOLAR PUBLICATIONS

  • 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
    2018
    Citations: 32
  • 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
    2012
    Citations: 26
  • Impact of big data and social media on society
    S Kumari
    Global Journal for Research Analysis 5, 437-438 , 2016
    2016
    Citations: 16
  • BREAST CANCER CLASSIFICATION USING BIG DATA APPROACH
    savita kumari sheoran
    Indian Journal of research 7 (01), 401-403 , 2018
    2018
    Citations: 14
  • Big data: A big boon for tourism sector
    SK Sheoran
    International Journal of Research in Advanced Engineering and Technology 3 … , 2017
    2017
    Citations: 11
  • 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
    2018
    Citations: 10
  • GeoWebCln: An Intensive Cleaning Architecture for Geospatial Metadata
    SK Sheoran, V Parmar
    Quaestiones Geographicae 41 (1), 51-62 , 2022
    2022
    Citations: 8
  • Applied Signal and Image Processing: Multidisciplinary Advancements
    R Qahwaji, R Qahwaji, R Green, EL Hines
    IGI Global , 2011
    2011
    Citations: 8
  • Comparative Analysis of Classification Efficiency of Quantum Machine Learning Algorithms
    SK Sheoran, V Yadav
    2024 IEEE International Conference on Computing, Power and Communication … , 2024
    2024
    Citations: 7
  • Autoregressive model for multivariate crime prediction
    R Yadav, SK Sheoran
    Decision Analytics Applications in Industry, 301-307 , 2020
    2020
    Citations: 6
  • 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
    2020
    Citations: 5
  • The role of deep learning in attaining the sustainable development goals
    N Yadav, SK Sheoran
    2024 First International Conference on Technological Innovations and Advance … , 2024
    2024
    Citations: 4
  • Machine learning based optimization scheme for detection of spam and malware propagation in twitter
    SK Sheoran, P Yadav
    International Journal of Advanced Computer Science and Applications 12 (2) , 2021
    2021
    Citations: 4
  • Robust evaluation of classical and quantum machine learning under noise, imbalance, feature reduction and explainability
    SK Sheoran, V Yadav, RK Sheoran
    Scientific Reports , 2025
    2025
    Citations: 3
  • Enhancing Data Classification with Hybrid QNNs and Quantum Feature Maps in Google Cirq
    SK Sheoran, V Yadav, RK Sheoran
    2025 Seventh International Conference on Computational Intelligence … , 2025
    2025
    Citations: 3
  • Analysis of criminal behavior through clustering approach
    R Yadav, SK Savita
    Int. J. Comput. Sci. Eng 6 , 2018
    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
    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
    2016
    Citations: 3
  • Big Data and social Media to improve the Quality of Higher education
    S Kumari
    IJCSMC 5 (3), 179-185 , 2016
    2016
    Citations: 3
  • Topological quantum error correction with semions
    S Verma, SS Kumari, RS Kumar
    Int. J. Phys. Math 6 (2), 44-47 , 2024
    2024
    Citations: 2