chetana prakash

@bietdvg.edu

Professor, CSE Department
Bapuji Institute of Engineering & Technology

chetana prakash


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https://researchid.co/chetanaprakash

EDUCATION

B.E. (Computer Science & Engineering)
M.S (BITS Pilani)
Ph.D (IIIT Hyderabad)

RESEARCH INTERESTS

Speech Signal, Fuzzy Technique, Web Data Mining, Data Mining, Image Processing, Computer Networks, IoT, ML, DL
23

Scopus Publications

706

Scholar Citations

11

Scholar h-index

11

Scholar i10-index

Scopus Publications

  • A web-based learning platform to assess student performance using online session activity engagement
    Shashirekha Hanumanthappa, Chetana Prakash
    Iaes International Journal of Artificial Intelligence, 2025
    Predicting students' performance and engagement is crucial for academic eLearning partners in colleges and universities as well as students themselves considering post-COVID-19 pandemic and university grant commission (UGC) dual degree regulation era. An educational system's data on students’ engagement in taking courses that are a significant component of an institution of higher learning with a cogent vertical syllabus can be used to make predictions. By examining how closely a student's course-taking actions correspond with the requirements of the syllabus, one can utilize the student's conduct in the classroom and online eLearning web tool as a predictor of future achievement. This paper presents a study that uses an eLearning web-based dataset to predict students' success throughout a series of online interactive sessions. The dataset records how students engage with each other during online lab work, including how many keystrokes they make, how long they spend on each task, and how well they perform on exams overall. The current methods lacks accuracy to assess student performance and engagement with high precision. In addressing this paper introduces novel multi-label ensemble learning (MLEL) using XGBoost (XGB) and K-fold cross validation. Experiment outcome shows the proposed (MLEL-XGB) achieves much improved outcome than other existing models.
  • Multi-label feature aware XGBoost model for student performance assessment using behavior data in online learning environment
    Shashirekha H
    Iaes International Journal of Artificial Intelligence, 2024
    In light of recent outbreaks like COVID19, the use of online-based learning streams (i.e., e-Learning systems) has increased significantly. Institutional efforts to boost student achievement have made precise predictions of academic success a priority. To analyze student sessions-streams and anticipate academic success, e-Learning platforms are starting to combine Datamining (DM) with Machine-Learning (ML) techniques. Recent research highlights the difficulties that ML-based methods have while dealing with unbalanced data. In tackling ensemble-learning, we combine several ML algorithms to select the most appropriate approach for the given data. Current ensemble-based approaches for predicting student achievement, nevertheless, don't do exceptionally well, particularly when it comes to multi-label classification, because they don't factor the relevance of features into their approaches. This study presents multi-label feature aware XGBoost (MLFA-XGB) method that improves upon the previously used ensemble-learning technique. The MLFA-XGB makes use of a robust cross-validation approach for gaining a deeper understanding of feature relationships. The experimental results demonstrate that in comparison with the state-of-the-art ensemble-based student achievement predictive approach, this suggested MLFA-XGB based approach provides much higher accuracy for prediction.
  • Machine learning based education data mining through student session streams
    Shashirekha Hanumanthappa, Chetana Prakash
    International Journal of Reconfigurable and Embedded Systems, 2024
    Recently, significant growth in using online-based learning stream (i.e., elearning systems) have been seen due to pandemic such as COVID-19. Forecasting student performance has become a major task as an institution is focusing on improving the quality of education and students' performance. Data mining (DM) employing machine learning (ML) techniques have been employed in the e-learning platform for analyzing student session streams and predicting academic performance with good effects. A recent, study shows ML-based methodologies exhibit when data is imbalanced. In addressing ensemble learning by combining multiple ML algorithms for choosing the best model according to data. However, the existing ensemblebased model does not incorporate feature importance into the student performance prediction model. Thus, exhibits poor performance, especially for multi-label classification. In addressing this, this paper presents an improved ensemble learning mechanism by modifying the XGBoost algorithm, namely modified XGBoost (MXGB). The MXGB incorporates an effective cross-validation scheme that learns correlation among features more efficiently. The experiment outcome shows the proposed MXGBabased student performance prediction model achieves much better prediction accuracy contrary to the state-of-art ensemble-based student performance prediction model.
  • IOT Security Against Network Anomalies through Ensemble of Classifiers Approach
    Saurav Verma, Chetana Prakash
    International Journal on Recent and Innovation Trends in Computing and Communication, 2023
    The use of IoT networks to monitor critical environments of all types where the volume of data transferred has greatly expanded in recent years due to a large rise in all forms of data. Since so many devices are connected to the Internet of Things (IoT), network and device security is of paramount importance. Network dynamics and complexity are still the biggest challenges to detecting IOT attacks. The dynamic nature of the network makes it challenging to categorise them using a single classifier. To identify the abnormalities, we therefore suggested an ensemble classifier in this study. The proposed ensemble classifier combines the independent classifiers ELM, Nave Byes (NB), and the k-nearest neighbour (KNN) in bagging and boosting configurations. The proposed technique is evaluated and compared using the MQTTset, a dataset focused on the MQTT protocol, which is frequently utilised in IoT networks. The analysis demonstrates that the proposed classifier outperforms the baseline classifiers in terms of classification accuracy, precision, recall, and F-score.
  • Analysis on Exposition of Speech Type Video Using SSD and CNN Techniques for Face Detection
    Manu Y. M., Chetana Prakash, S. Santhosh, Shaik Shafi, K. Shruthi
    Eai Springer Innovations in Communication and Computing, 2023
  • Attention-based position-aware framework for aspect-based opinion mining using bidirectional long short-term memory
    Azizkhan F Pathan, Chetana Prakash
    Journal of King Saud University Computer and Information Sciences, 2022
    Aspect-based Opinion Mining is a form of fine-grained Sentiment Analysis and it models the semasiological relationship between aspect terms and context words in a sentence. The presence of a variety of context words has a significant impact on a sentence's sentiment polarity. As a result, while designing a model, it is necessary to consider the interaction of aspects and context words. Although existing approaches have taken into account an aspect’s position in a sentence, much of the research works have not explored the use of Sentiment Lexicons with the Deep Learning algorithms. In this paper, we propose a framework for an Attention-based position-aware Bidirectional Long Short-Term Memory network for Aspect-based Opinion Mining that incorporates a Sentiment Intensity Lexicon. The aspect word’s pre-trained vector is adjusted to be closer to semantically and sentimentally similar nearest neighbors and further away from sentimentally dissimilar neighbors. The proposed framework calculates aspect weights by concatenating the external knowledge in the form of lexicon sentiment intensity scores with word embeddings and position information. The framework experiments on the SemEval 2014 dataset. The results of the experiments illustrate that injecting external knowledge into the Bidirectional Long Short-Term Memory network can improve classification accuracy significantly.
  • Cross-Domain Aspect Detection and Categorization using Machine Learning for Aspect-based Opinion Mining
    Azizkhan F Pathan, Chetana Prakash
    International Journal of Information Management Data Insights, 2022
    There is an increase in the development of social media and electronic commerce sites day by day. In order to express their opinions about the products purchased user's write comments, messages and reviews. The reviews present in the e-commerce sites are also increasing. Users find difficulty in getting appropriate information about the right topic from this large data. Aspect-based Opinion Mining (ABOM) helps users in this regard. In many real-world applications ABOM is used to get the details about the aspects of entities, where the opinion is expressed for those aspects and entities. One of the key elements of ABOM is Aspect extraction. Unsupervised Machine Learning approach has been used to extract aspects from the reviews as it does not require pre-labelled data. In this regard Latent Dirichlet Allocation (LDA) and Latent Semantic Analysis (LSA) are two most commonly used unsupervised Topic Modeling approaches. The topics are extracted from three different datasets such as Amazon Mobile Reviews, Hotel Reviews and IMDb Movie Reviews using LDA and LSA algorithms. These extracted topics are aspects of our interest. The results of topic modeling algorithms are quite difficult to be interpreted by the common user. The different visualization methods are used to display the results of topic modeling algorithms in an interactive way. Two different multi-class classifiers such as Multinomial Naive Bayes (MNB) and Support Vector Machine (SVM) have been constructed for aspect categorization. These classifiers are evaluated by considering the evaluation measures such as Precision, Recall and F1 score. As a result, SVM classifier has good performance than MNB classifier for aspect categorization task of aspect-based opinion mining.
  • Implementation of New Approach to Secure IoT Networks with Encryption and Decryption Techniques
    Aditya Sarin, Deveshi Thanawala, Saurav Verma, Chetana Prakash
    2020 11th International Conference on Computing Communication and Networking Technologies Icccnt 2020, 2020
    The diversity of the internet can be fascinating with our everyday devices getting automated. However, such technology of connecting everything to the internet can actually be daunting. This data could easily be attacked by malicious users and hence hangs the usage of such technologies in a precarious condition. To prevent such attacks, we have used AES algorithm to secure data bits and also designed a two-stage encryption and decryption algorithm. This algorithm was successfully tested by transmitting data bits through a channel between two wireless sensor nodes for five test cases. The model is tested in such a way that it can be universally applicable to all IoT networks.
  • Noise Reduction using Multilevel Hybrid Filters for Ultrasound Images: A Comparative Study
    Kavitha G., Chetana Prakash
    Proceedings of the 5th International Conference on Inventive Computation Technologies Icict 2020, 2020
    Medical imaging has become a very important non-invasive diagnosis tool for various diseases. During image acquisition, they get acquainted with noise because of modality and/or because of body conditions such as patient’s position or body fat. Most common noise in ultrasound is speckle, CT and MRI are motion and electrical noises. And other additional noise can also be present such as salt and pepper, Gaussian, Poisson. These noises degrade image quality. The only expert radiologist can make an appropriate diagnosis. Hence it is very important to perform de-noising. Many techniques are present for de-noising which are basically dependent on noise type. Here an attempt is made to remove speckle noise using multilevel hybrid filters. Ultrasound images of the common carotid artery are degraded by speckle noise and then de-noised using the median, wiener, NLM, Homorphic, Bilateral and hybrid filter are applied. Performance of these algorithms is measured using PSNR, MSE, SSIM and ROC curve is drawn. Results show that the Median filter With Bilateral filter has better performance.
  • An Internet of Things (IoT) Architecture for Smart Agriculture
    Saurav Verma, Rahul Gala, S. Madhavan, Sanchit Burkule, Swapnil Chauhan, Chetana Prakash
    Proceedings 2018 4th International Conference on Computing Communication Control and Automation Iccubea 2018, 2018
    Agriculture is one major and important sector for the growth of economy for any country. As per the current scenarios, various problems are present in agriculture like techniques which are used currently are not efficient, requirement of larger manpower and appropriate time for irrigation and spreading of fertilizer to yield. Internet of Things (IoT) is latest technology for smart farming to enhance efficiency, productivity and resolve various issues present in agriculture. IoT network consist of various sensor node which is used to monitor soil acidity level, temperature, and other variables. In this paper, the steps involved for agriculture are discussed and mainly focus on use of IoT in agriculture i.e. in proposed architecture which leads to growth of agriculture exponentially and the economy.
  • Internet of Things (IoT): A vision, architectural elements, and security issues
    Shivangi Vashi, Jyotsnamayee Ram, Janit Modi, Saurav Verma, Chetana Prakash
    Proceedings of the International Conference on Iot in Social Mobile Analytics and Cloud I Smac 2017, 2017
  • Understanding Trust and Privacy of Big Data in Social Networks - A Brief Review
    H. Shashi Rekha, Chetana Prakash, G. Kavitha
    Proceedings 2014 3rd International Conference on Eco Friendly Computing and Communication Systems ICECCS 2014, 2014
  • Analysis of acoustic events in speech signals using bessel series expansion
    Chetana Prakash, Dhananjaya N. Gowda, Suryakanth V. Gangashetty
    Circuits Systems and Signal Processing, 2013
  • Fourier-Bessel cepstral coefficients for robust speech recognition
    Chetana Prakash, Suryakanth V. Gangashetty
    2012 International Conference on Signal Processing and Communications Spcom 2012, 2012
  • Fourier - Bessel based cepstral coefficient features for text-independent speaker identification
    Proceedings of the 5th Indian International Conference on Artificial Intelligence Iicai 2011, 2011
  • Exploring Bessel features for detection of glottal closure instants
    Proceedings of the Annual Conference of the International Speech Communication Association Interspeech, 2011
  • Bessel features for detection of voice onset time using AM-FM signal
    International Conference on Systems Signals and Image Processing, 2011
  • Bessel transform for image resizing
    International Conference on Systems Signals and Image Processing, 2011
  • Detection of glottal closure instants from Bessel features using AM-FM signal
    International Conference on Systems Signals and Image Processing, 2011
  • Bessel features for estimating number of speakers from multispeaker speech signals
    International Conference on Systems Signals and Image Processing, 2011
  • Speech enhancement using ICA with Bessel features
    International Conference on Systems Signals and Image Processing, 2011
  • Palmprint recognition: Two level structure matching
    IEEE International Conference on Neural Networks Conference Proceedings, 2006
  • Binary tree based linear time fingerprint matching
    Mayur D Jain, S Nalin Pradeep, C Prakash, Balasubramanian Raman
    Proceedings International Conference on Image Processing Icip, 2006

RECENT SCHOLAR PUBLICATIONS

  • Harmony in numbers: unifying management and accounting for financial success
    CSS Prakash, A Sultana, P Mehta, HS Kumar, BMA Defalla, P Divakaran, ...
    Revista de Gestão Social e Ambiental 18 (9), 1-15 , 2024
    2024
    Citations: 4
  • Alveolar Bone Loss Detection and Localization in Dental X-Ray Images using YOLOv5
    CP G. A. Babitha and G. H. Kiran Kumar G. C. Jyothi
    Asian Journal of Computer Science and Technology 12 (1), 41-54 , 2023
    2023
    Citations: 1
  • Deep Learning Approach for Detection of Dental Caries in X -Ray Images
    CP G. A. Babitha and G. H. Kiran Kumar G. C. Jyothi
    International Journal of Scientific Development and Research (IJSDR) 8 (6 … , 2023
    2023
  • Computer vision-based assistive technology for blind and visually impaired people: A deep learning approach
    GM Roopa, C Prakash, N Pradeep
    Computer Assistive Technologies for Physically and Cognitively Challenged … , 2023
    2023
    Citations: 4
  • Noise estimation and type identification in natural scene and medical images using deep learning approaches
    G Kavitha, C Prakash, M Alhomrani, N Pradeep, AS Alamri, PK Pareek, ...
    Contrast Media & Molecular Imaging 2023 (1), 3923667 , 2023
    2023
    Citations: 7
  • Cross-domain aspect detection and categorization using machine learning for aspect-based opinion mining
    AF Pathan, C Prakash
    International Journal of Information Management Data Insights 2 (2), 100099 , 2022
    2022
    Citations: 25
  • Attention-based position-aware framework for aspect-based opinion mining using bidirectional long short-term memory
    AF Pathan, C Prakash
    Journal of King Saud University-Computer and Information Sciences 34 (10 … , 2022
    2022
    Citations: 17
  • Air Quality Monitoring System Using Linear Regression and Machine Learning
    DNCR Vasudeva M B , Pradeep K , Dr. Chetana Prakash
    International Research Journal of Engineering & Technology 9 (6), 1460-1463 , 2022
    2022
  • Comparison analysis of CNN, SVC and random forest algorithms in segmentation of teeth X-ray images
    GC Jyothi, C Prakash, GA Babitha, GHK Kumar
    Asian Journal of Computer Science and Technology 11 (1), 40-47 , 2022
    2022
    Citations: 4
  • Sign Language Recognition System
    DCP Akriti Goyal, Deepanshu Dhar, Paras A Nair, Chirag Saini, Supreetha S M
    International Journal of Engineering Research and Technology 10 (11), 315-317 , 2022
    2022
  • Unsupervised Aspect Extraction Algorithm for opinion mining using topic modeling
    CP Azizkhan F Pathan
    Global Transaction Proceedings 2 (2021), 492-499 , 2021
    2021
    Citations: 40
  • Unsupervised Aspect Extraction Algorithm for Opinion Mining using Topic Modeling
    AFP Chetana Prakash
    International Conference on Computing System and Its Applications (ICCSA - 2021) , 2021
    2021
  • Lung Cancer Detection in Radiology Images using CNN
    SSK Chetana Prakash, Sheetal P, Meghana H D, Vidyashree M B
    International Journal for Research in Applied Science & Engineering … , 2021
    2021
  • Cloud Based Application for Prediction of Natural Disasters
    LEJ Chetana Prakash
    International Journal for Research in Applied Science & Engineering … , 2021
    2021
  • Video Based Suspicious Human Behaviour Recognition System
    CM Chetana Prakash, Aneesa Banu, Deeksha J Udasi, Gousiya Banu
    International Journal for Research in Applied Science & Engineering … , 2021
    2021
  • Segmentation Algorithm for Dental Caries X-Ray Images
    JGC Chetana Prakash
    GIS Science Journal 8 (Issue 7, July 2021), ISSN NO: 1869 - 9301/www … , 2021
    2021
  • Novel Hybrid Architecture of Infotainment for Streaming Signals in Vehicular Network
    S Reshma, C Prakash, M Rafi
    2021
    Citations: 1
  • Analysis on Exposition of Speech Type Video using SSD and CNN Techniques for Face Detection
    SK Dr. Chetana Prakash, Manu Y M, Santhosh S Shaik Shafi
    Studies in Computational Intelligence , 2021
    2021
  • Identification of Leaf Disease and Pesticides Recommendation Using ML
    PC Chetana Prakash
    International Journal of Advanced Research in Science, Engineering and … , 2020
    2020
  • AN UNSTRUCTURED TO STRUCTURED DATA CONVERSION USING MACHINE LEARNING ALGORITHM IN INTERNET OF THINGS (IOT)
    KJ Chetana Prakash, Saurav Verma
    3 RD INTERNATIONAL CONFERENCE ON INNOVATIVE COMPUTING AND COMMUNICATION … , 2020
    2020
    Citations: 14

MOST CITED SCHOLAR PUBLICATIONS

  • Internet of Things (IoT): A vision, architectural elements, and security issues
    S Vashi, J Ram, J Modi, S Verma, C Prakash
    2017 international conference on I-SMAC (IoT in Social, Mobile, Analytics … , 2017
    2017
    Citations: 400
  • An internet of things (IoT) architecture for smart agriculture
    S Verma, R Gala, S Madhavan, S Burkule, S Chauhan, C Prakash
    2018 fourth international conference on computing communication control and … , 2018
    2018
    Citations: 63
  • Unsupervised Aspect Extraction Algorithm for opinion mining using topic modeling
    CP Azizkhan F Pathan
    Global Transaction Proceedings 2 (2021), 492-499 , 2021
    2021
    Citations: 40
  • Cross-domain aspect detection and categorization using machine learning for aspect-based opinion mining
    AF Pathan, C Prakash
    International Journal of Information Management Data Insights 2 (2), 100099 , 2022
    2022
    Citations: 25
  • Attention-based position-aware framework for aspect-based opinion mining using bidirectional long short-term memory
    AF Pathan, C Prakash
    Journal of King Saud University-Computer and Information Sciences 34 (10 … , 2022
    2022
    Citations: 17
  • Bessel transform for image resizing
    G Mohan P, C Prakash, SV Gangashetty
    2011 18th International Conference on Systems, 70 , 2011
    2011
    Citations: 16
  • AN UNSTRUCTURED TO STRUCTURED DATA CONVERSION USING MACHINE LEARNING ALGORITHM IN INTERNET OF THINGS (IOT)
    KJ Chetana Prakash, Saurav Verma
    3 RD INTERNATIONAL CONFERENCE ON INNOVATIVE COMPUTING AND COMMUNICATION … , 2020
    2020
    Citations: 14
  • Bessel features for estimating number of speakers from multispeaker speech signals
    PVA Kumar, L Balakrishna, C Prakash, SV Gangashetty
    2011 18th International Conference on Systems, Signals and Image Processing, 1-4 , 2011
    2011
    Citations: 14
  • Bessel features for detection of voice onset time using AM-FM signal
    C Prakash, N Dhananjaya, SV Gangashetty
    2011 18th International Conference on Systems, Signals and Image Processing, 1-4 , 2011
    2011
    Citations: 14
  • Fourier-Bessel cepstral coefficients for robust speech recognition
    C Prakash, SV Gangashetty
    2012 international conference on signal processing and communications (SPCOM … , 2012
    2012
    Citations: 13
  • Fourier-Bessel based Cepstral Coefficient Features for Text-Independent Speaker Identification.
    C Prakash, SV Gangashetty
    IICAI, 913-930 , 2011
    2011
    Citations: 11
  • Analysis of acoustic events in speech signals using Bessel series expansion
    C Prakash, DN Gowda, SV Gangashetty
    Circuits, Systems, and Signal Processing 32 (6), 2915-2938 , 2013
    2013
    Citations: 9
  • Optical, piezoelectric, leakage current and polarization fatigue studies of NBT-KNN ceramics near MPB
    S Swain, M Chandrasekhar, P Kumar, C Prakash
    Ferroelectrics 516 (1), 185-192 , 2017
    2017
    Citations: 8
  • Bessel transform for image resizing
    C Prakash, SV Gangashetty
    2011 18th International Conference on Systems, Signals and Image Processing, 1-4 , 2011
    2011
    Citations: 8
  • Noise estimation and type identification in natural scene and medical images using deep learning approaches
    G Kavitha, C Prakash, M Alhomrani, N Pradeep, AS Alamri, PK Pareek, ...
    Contrast Media & Molecular Imaging 2023 (1), 3923667 , 2023
    2023
    Citations: 7
  • Understanding trust and privacy of big data in social networks-a brief review
    HS Rekha, C Prakash, G Kavitha
    2014 3rd international conference on eco-friendly computing and … , 2014
    2014
    Citations: 7
  • Detection of glottal closure instants from Bessel features using AM-FM signal
    C Prakash, N Dhananjaya, SV Gangashetty
    2011 18th International Conference on Systems, Signals and Image Processing, 1-4 , 2011
    2011
    Citations: 7
  • IMPLEMENTATION OF NEW APPROACH TO SECURE IOT NETWORKS WITH ENCRYPTION AND DECRYPTION TECHNIQUES
    DT Chetana Prakash, Saurav Verma, Aditya Sarin
    11th INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND NETWORKING … , 2020
    2020
    Citations: 6
  • Relaxation and conduction mechanism of BNT-KNN ceramics by impedance study
    M Chandrasekhar, P Kumar, C Prakash, A Kumar
    Ferroelectrics 517 (1), 58-65 , 2017
    2017
    Citations: 6
  • Harmony in numbers: unifying management and accounting for financial success
    CSS Prakash, A Sultana, P Mehta, HS Kumar, BMA Defalla, P Divakaran, ...
    Revista de Gestão Social e Ambiental 18 (9), 1-15 , 2024
    2024
    Citations: 4

Publications

1. A Comparative study of Median, ANW, NLM and proposed Hybrid Filtering Technique using Median and ANW Filter for Medical Images, (IPASJ International
Journal of Computer Science (IIJCS))
2. Implementation of New Approach to Secure IoT Networks with Encryption and Decryption Techniques, IEEE 49239
3. A Framework for Hierarchical Big Image Data , IJIRSET
4. Advancement in infotainment system in automotive sector with vehicular cloud network and current state of art (IJECE)
5. An Internet of things (IoT) architecture for Smart Agriculture ( 978-1-5386-5257-2/18/$31.00 ©2018 IEEE)
6. Big Data Mining from Social Networking Services using Spectral Clustering Algorithm (IJIRCCE)
7. Privacy Preserving Mechanism for Mobile Healthcare Emergency (IJARSET)
8. Internet of Things (IoT) A vision, Architectural Elements and Security Issues" , IEEE International Conference on I-SMAC
( IoT in Social, Mobile, Analytics & Cloud) (I-SMAC-2017)
9. Survey on Infotainment System for Vehicular Adhoc Networks" 3rd National Conference on Recent Trends in Electronics & Communication – 2017
(NCRTEC-2017)
10. Comparative study of Median, ANW, NLM and proposed Hybrid Filtering Technique using , Median and ANW Filter for Medical Images", IPASJ, International Journal of Computer Science
11. Privacy Preserving Mechanism for Mobile Healthcare Emergency" , International Journal of Advanced Research in Science , Engineering Technology
12.An Internet of things (IoT) architecture for smart Agricu