Monika Mangla

Scopus Publications

Colon cancer detection using VGG16 and XAI methods
Anvaya Solanki, Dewansh Gopani, Monika Mangla, Deepak Kumar
Connecting Intelligence Trends in Computation and Data Communication, 2026
Colon cancer is responsible for a high percentage of cancer mortality throughout the world, and therefore there was a need to create early and better diagnosis methods. The conventional methods were not unambiguous enough and were “black boxes,” which compromised clinical adoption and endorsement. In this paper, we attempt to address these issues by creating a VGG16-tailored convolutional neural network on a balanced dataset of 10,000 histopathological images of 5,000 colon adenocarcinomas and 5,000 benign tissue samples. We used the latest breakthroughs in deep learning in medical imaging to include XAI techniques which are Grad-CAM, LIME and SHAP to provide both visual and quantitative explanations of model decisions. This illuminates the attributes behind the classification, which are concealed usually. Our work highlights the efficiency of combining high-performing CNN architectures with explainable artificial intelligence to enhance the early detection of colon cancer and facilitate clinical diagnosis with increased transparency and reliability.
Federated Learning for IoT: A Privacy-Preserving Approach to Intelligent Edge Systems
Nonita Sharma, Monika Mangla, Ravi Sharma, Manik Rakhra
Lecture Notes in Computer Science, 2026
Fit AI: A Deep Learning-Based Fitness Coaching System with Real-Time Pose Detection
Dhwani Dalal, Dipti Agarwal, Hetvi Patel, Archie Mehta, Monika Mangla, Monali Sankhe
6th Biennial International Conference on Nascent Technologies in Engineering Icnte 2026, 2026
In recent years, Artificial Intelligence (AI) has reformed several fields, including health and physical fitness. Fit AI is an AI-powered virtual fitness coach created to support mental and physical well-being. TensorFlow’s MoveNet model enables Fit AI to track body movements in real time and respond with corrective feedback. Through this continuous monitoring, users can improve form and reduce the risk of injury. It delivers guidance without the high cost of personal coaching, helping more people access fitness support. Fit AI was evaluated across three performance metrics: training accuracy (92.3%), testing accuracy (90.4%), and user satisfaction (93.0%). These findings show that AI-based fitness tools can offer accurate, personalized, and affordable training experiences.
FinFlow: Enhancing Portfolio Performance Through Risk Optimization
Ruchit Sheth, Shreya Khandekar, Vedica Mrudul, Monali Sankhe, Monika Mangla, Pravin Hole
6th Biennial International Conference on Nascent Technologies in Engineering Icnte 2026, 2026
The growing complexity of financial markets has made personal asset management a major challenge for individual investors. While robo-advisors and digital platforms aim to simplify investment decisions, they often use fixed allocation rules and miss important factors like behavioral risk, long-term stability, and market sentiment. This paper presents FinFlow, a Personal Asset Management System that combines machine learning, sentiment analysis, and financial optimization into one framework. The system is delivered through a web-based interface, offering investors personalized recommendations and an interactive dashboard. Evaluation using simulated user profiles and historical market data shows that FinFlow creates allocations that match investor preferences, reduces volatility through diversification, and increases responsiveness to sentiment-driven changes. The findings show the potential of AI-driven systems to fill the gap between the tools used by institutions and the needs of retail investors.
Symmetry-guided explainable deep learning for colon cancer diagnosis: model benchmarking, cross-validation, statistical analysis, and explainability via ablation studies
Anvaya Solanki, Dewansh Gopani, Monika Mangla, Nonita Sharma, Mu’azu Jibrin Musa, R. S. M. Lakshmi Patibandla
Frontiers in Artificial Intelligence, 2026
Introduction Histopathological tissue reveals natural radial and bilateral symmetry in glandular structures, which becomes progressively disrupted during malignant transformation. Leveraging this observation, this work presents a VGG16-based deep learning model enriched with symmetry-aware interpretation for early detection of Colon Adenocarcinoma. The traditional approaches are not straightforward enough and acts as “black boxes” diminishing their clinical adoption and acceptance in real-world scenario. Current research work uses the most recent breakthroughs in deep learning on medical imaging and integrates Explainable AI strategies such as LIME, SHAP, and Grad-CAM into the model to interpret how cancer-induced symmetry distortions influence model decisions. Methods This work is experimented on a balanced dataset of 10,000 histopathological scans, including 5,000 Colon Adenocarcinoma tissue samples and 5,000 Benign Colon Tissue samples. This research aims to shed light on how benign tissues preserve consistent symmetric glandular patterns; while cancerous samples exhibit pronounced asymmetry, irregular boundaries, and disrupted structural repetition. Authors further aim to quantify these differences using lightweight 2D symmetry indices, demonstrating a clear separation between normal and malignant tissues. Results and Discussion Current research presents a highly precise model for the diagnosis of colon cancer using a VGG16 CNN that achieves an encouraging test accuracy of 99.85%. The model exhibited very high precision, recall, and F1-scores for both classes, normal and cancer, as demonstrated by the classification report. Among various XAI techniques, Grad-CAM demonstrated speed and scalability making it an appropriate choice for its large-scale deployment in healthcare. SHAP, though computationally costly, offered theoretical robustness and great insight. LIME was handy in local interpretability, especially convenient in debugging individual predictions.
Blockchain-Enabled Electronic Health Record System with Integrated Machine Learning for Kidney Disease Classification
Radhika Patel, Isha Patel, Moksha Shah, Kriya Parmar, Monali Sankhe, Monika Mangla
6th Biennial International Conference on Nascent Technologies in Engineering Icnte 2026, 2026
Electronic Health Records (EHR) are vital to modern healthcare, offering more effective means of electronically managing and accessing patient medical records. Using blockchain technology, this EHR makes use of Ethereum smart contracts for access and decentralized storage to provide security, transparency, and the ability to manage patient medical records in a tamper-proof way. The Interplanetary File System (IPFS), in conjunction with Pinata, provides immutable data storage for medical files. This EHR system combines smart contract-based access, decentralized storage of patient information, and a Web3 interface to support safe wardship of patient medical records while enhancing security and reducing administrative burden. It also includes a convolutional neural network (CNN) machine learning algorithm to harness the patient’s potentially harmful internal kidney conditions. The end product is an intelligent, data-driven, and secure EHR system that increases patient confidentiality of health information in settings with limited resources.
Ensemble of Temporal Weighting, Causal Inference, and Hierarchical Attribution towards SHAP Optimization
Archana Salaria, Manik Rakhra, Nonita Sharma, Monika Mangla, Fernando Moreira, Nishan Singh Bala
Journal of Visualized Experiments, 2025
During the past few years, the need for transparency and interpretability has been intensified owing to significant advancements in data-driven models, leading to the emergence of Explainable Artificial Intelligence (XAI). Several traditional XAI approaches are prevalent; however, these have limited competence in interpreting dynamic relations. The current research aims to address this limitation by proposing a novel Ensemble SHapley Additive exPlanations (SHAP) framework that focuses on temporal weighting, causal inference, hierarchical attribution, and interpretability optimization referred to as TCHSHAP. TCHSHAP prioritizes current information over historical information by temporal weighting through exponential decay. Further, causal inference separates correlation from causality to gain practical insights. Additionally, hierarchical attribution allows insights at granular (region level) and aggregated levels (feature-group impacts). These approaches are integrated to achieve a more interpretable and explainable model. To validate the efficacy of the proposed model, we carry out an experiment on the crop yield dataset collected from Kaggle. Ahead of experimental evaluation, data preprocessing is performed using one-hot encoding. Data normalization is done by min-max scaling, and outliers are removed through the Interquartile range. For the sake of experimental evaluation, the authors used the SHAP XAI model for Random Forest. When assessing the efficacy of the proposed TCHSHAP model, it is observed that while the average prediction for traditional SHAP is 161.137, it escalates to 161.506 after incorporating temporal weighting and causal inference, advocating the effectiveness of employing temporal and causal significance. Additionally, during hierarchical attribution, it is observed that agricultural features have the strongest dominance over the target variable. This dominance is followed by geographical and environmental factors in order. Thus, the obtained results authorize the efficacy of the proposed approach towards enhancing the global and local interpretability, strengthening the user's trust in model predictions. The current work offers ways to improve transparency and interpretability without affecting model performance. The suggested model also enables interpretable and efficient regression modelling in complex, data-driven applications, enabling its widespread application in real-world settings.
A novel deep copy stacked ensemble optimization technique for optimal predictive maintenance of air compressors
Eshita Ojha, Nonita Sharma, Monika Mangla
Iran Journal of Computer Science, 2025
EMPLOYING GENETIC ALGORITHM INSPIRED HYPERPARAMETER OPTIMIZATION IN MOBILE NET V2 ARCHITECTURE
Baljinder Kaur, Manik Rakhra, Nonita Sharma, Monika Mangla
Proceedings on Engineering Sciences, 2025
This paper presents a novel approach for hyperparameter optimization for the MobileNetV2 architecture using a genetic algorithm. The proposed approach aims to automate the hyperparameter tuning leading to performance enhancement. This automated approach conserves the computational overheads involved in traditional hyperparameter tuning methods. This automated method for hyperparameter tuning is the result of significant advancement in the domain of deep learning models and eventually offers a scalable and efficient solution for developing high-performance mobile applications. This understanding will surely aid authors to devise an intriguing solution to address the involved challenges. Authors have provided 2-step solution where first part proposes a novel genetic algorithm based hyperparameter optimization followed by creation of a lightweight deep learning architecture, the second step of the solution. Further, the authors also aim to devise a mobile application that widens the scope of real-life application of the case study. Here, authors have undertaken the case study of poultry disease identification to evaluate the effectiveness and efficiency of proposed solution.
Modernizing and Validating Safety Product
Neha Agarwal, Monika Mangla, Richa Sharma, Sharvari Patil, Priyanca Gonsalves
Lecture Notes in Electrical Engineering, 2025
Optimizing Revenue Generation in E-Commerce: An Analysis of Customer Purchase Intent Using Machine Learning Technique
Rahul Kalathia, Monika Mangla, Nonita Sharma, Vaishali Mehta, Manik Rakhra
Icdt 2025 3rd International Conference on Disruptive Technologies, 2025
Bridging Precision and Transparency: XAI Models for Predicting Students Depression
Monika Mangla, Balajee Maram, Vaishali Mehta Wadhwa, Jyoti Garg, Aditi Sharma, Amol Dhumane
2025 IEEE 6th Global Conference for Advancement in Technology Gcat 2025, 2025
Challenges and Solutions in Internet of Things-Based Smart Applications
Narendra Shekokar, Subhash K. Shinde, Smita Sanjay Ambarkar, Antonis Michalas, Monika Mangla, Achamma Thomas
Challenges and Solutions in Internet of Things Based Smart Applications, 2025
Optimizing Digital Storage with Neural Networks: Classification, Anomaly Detection, and Forecasting
Rohit Rai, Hargun Singh Chandhok, Akash Manna, Monika Mangla, Monali Sankhe, Pravin Hole
2025 International Conference on Sustainability Innovation and Technology Icsit 2025, 2025
Longformer-Powered Sop Assessment and University Admission Likelihood Predictor
Dhruv Nariani, Dhruv Kothari, Atharva Narvekar, Divya Shah, Monika Mangla, Khushbu Trehan
2025 International Conference on Sustainability Innovation and Technology Icsit 2025, 2025
AI-Driven Optical Intelligence for Modern Warfare Command and Control
Rahul Chougule, Varad Patil, Amey Rane, Monika Mangla, Pravin Hole, Monali Sankhe
2025 9th International Conference on Computing Communication Control and Automation Icccbea 2025, 2025
Early detection of gynecological malignancies using ensemble deep learning models: ResNet50 and inception V3
Chetna Vaid Kwatra, Harpreet Kaur, Monika Mangla, Arun Singh, Swapnali N. Tambe, Saiprasad Potharaju
Informatics in Medicine Unlocked, 2025
A Unified Distributed Version Control System for SQL and Graph Databases
Monali Sankhe, Monika Mangla, Preksha Shah, Prince Doshi, Jeniel Shah, Deep Vyas
2025 9th International Conference on Computing Communication Control and Automation Icccbea 2025, 2025
DNA Inspired Chaotic Encryption with Pixel Shuffling (DICEPS)
Shantanu Dhar, Yuvraj Agarwal, Shlok Pete, Shawneil Rodrigues, Ramchandra Mangrulkar, Monika Mangla
2025 5th Asian Conference on Innovation in Technology Asiancon 2025, 2025
IndoorNavX: ARCore-Powered Markerless Indoor Navigation
Meer Mehta, Kushal Mehta, Kushagra Chauhan, Monika Mangla, Monali Sankhe, Pravin Hole
2025 IEEE International Conference on Smart Power Energy Renewables and Transportation Spert 2025 Proceedings, 2025
NON-DOMINATED SORTING GENETIC ALGORITHM-II BASED PARETO-FRONT MULTI OBJECTIVE OPTIMIZATION FOR BALANCING SUSTAINABILITY AND PRODUCTIVITY
Archana Archana, Manik Rakhra, Nonita Sharma, Monika Mangla, Deepthi Godavarthi, Putta Durga, Nishan Singh Bala
Proceedings on Engineering Sciences, 2025
Modelling of Diabetic Cases for Effective Prevalence Classification
Shrey Shah, Monika Mangla, Nonita Sharma, Tanupriya Choudhury, Maganti Syamala
Eai Endorsed Transactions on Pervasive Health and Technology, 2024
Machine Learning Based Assessment and Predictive Analysis of In-Vitro Fertilization Success Rate
Vaishali Mehta, Monika Mangla, Nonita Sharma, Manik Rakhra, Tanupriya Choudhury, Garigipati Rama Krishna
Eai Endorsed Transactions on Pervasive Health and Technology, 2024
An Ensemble Framework for Predictive Maintenance of WaterPumps
Eshita Ojha, Nonita Sharma, Monika Mangla
2nd International Conference on Intelligent Data Communication Technologies and Internet of Things Idciot 2024, 2024
Employing Machine Learning Models in Prediction of Harmful Gases from Agri-Waste
Vaishali Mehta, Monika Mangla, Neera Batra
Lecture Notes in Electrical Engineering, 2024
A Hybrid Fuzzy Factor Analysis Model for Evaluation of Fiscal Proficiency
Poonam, Monika Mangla, Nonita Sharma, Mohamed Sirajudeen Yoosuf
Eai Endorsed Transactions on Scalable Information Systems, 2024
Individualized Guidance in Yoga Practice: A Comparative Analysis of Technology Solutions
Miti Gosalia, Ronik Dedhia, Sakshi Doshi, Richa Sharma, Monika Mangla
2024 International Conference on Electrical Electronics and Computing Technologies Iceect 2024, 2024
A Comparative Analysis and Statistical Inference of Diabetes Cases
Shreya Singhal, Shriyaa Gupta, Nonita Sharma, Monika Mangla, Manik Rakhra
Lecture Notes in Electrical Engineering, 2024
Generative AI based Interior Designing
Karan Thakkar, Kunaal Vadgama, Krish Ranawat, Richa Sharma, Monika Mangla
2024 International Conference on Electrical Electronics and Computing Technologies Iceect 2024, 2024
Employing Machine Learning based Majority Voting Classifier for Explicit Content Detection in Music
Prathmesh Ghatol, Yash Shah, Rucha Gavaskar, Monika Mangla, Richa Sharma
Indiscon 2024 5th IEEE India Council International Subsections Conference Science Technology and Society, 2024
Lung Disease Detection from Chest X-Ray Using GANs
Richa Sharma, Monika Mangla, Sharvari Patil, Priyanca Gonsalves, Neha Agarwal
2nd International Conference on Intelligent Data Communication Technologies and Internet of Things Idciot 2024, 2024
A Review on Prediction and Diagnosis of Mental Health Disorders Using Quantum Machine Learning Classifier
Poonam, Vaishali Mehta, Mutiq Katib Alrashidi, Monika Mangla, Manik Rakhra, Nonita Sharma
2024 International Conference on Cybernation and Computation Cybercom 2024, 2024
FinTech Edge: Utility Computing & Artificial Intelligence Technologies for Smart Financial Acquisition & Blockchain in the Financial Industries
Sandeep Singh, Tiyas Sarkar, Monika Mangla, Manik Rakhra, Amanpreet Singh, Kapil Jairath
Proceedings of International Conference on Contemporary Computing and Informatics Ic3i 2024, 2024
Online Transaction Fraud Detection Using Machine Learning
Ayushi Pasrija, Pooja Dahiya, Nonita Sharma, Monika Mangla
Aip Conference Proceedings, 2023
Inferential Analysis of Amazon’s Top 50 Bestselling Books
Rishika, Sneha Singh, Nonita Sharma, Monika Mangla
Aip Conference Proceedings, 2023
Inferential Statistics and Visualisation Analysis of Automobile Industry
Aarna Singhal, Kusha Varshney, Nonita Sharma, Monika Mangla, Inderdeep Kaur
Aip Conference Proceedings, 2023
Geospatial multivariate analysis of COVID-19: a global perspective
Nonita Sharma, Sourabh Yadav, Monika Mangla, Anee Mohanty, Suneeta Satpathy, Sachi Nandan Mohanty, Tanupriya Choudhury
Geojournal, 2023
Deep Learning Framework for Identification of Skin Lesions
Nonita Sharma, Monika Mangla, M Mohamed Iqbal, Sachi Nandan Mohanty
Eai Endorsed Transactions on Pervasive Health and Technology, 2023
Scope of Machine Learning and Blockchain in Cyber Security
Rohini Patil, Monika Mangla, Smita Bansod
Intelligent Approaches to Cyber Security, 2023
Supervised Learning Techniques for Sentiment Analysis
Nonita Sharma, Monika Mangla, Sachi Nandan Mohanty
Lecture Notes in Networks and Systems, 2023
Classification and Comparative Analysis of Earth's Nearest Objects using Machine Learning Models
Proceedings of the 17th Indiacom 2023 10th International Conference on Computing for Sustainable Global Development Indiacom 2023, 2023
Comparison of Transfer Learning Techniques to Classify Brain Tumours Using MRI Images †
Jayneet Jain, Mihika Kubadia, Monika Mangla, Prachi Tawde
Engineering Proceedings, 2023
Multivariate Analysis and Comparison of Machine Learning Algorithms: A Case Study of Cereals of America
Rashika Gupta, E. Lavanya, Nonita Sharma, Monika Mangla
Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering Lnicst, 2023
Breast cancer classification using snapshot ensemble deep learning model and t-distributed stochastic neighbor embedding
Nonita Sharma, K. P. Sharma, Monika Mangla, Rajneesh Rani
Multimedia Tools and Applications, 2023
Inferential Statistics and Visualization Techniques for Aspect Analysis
Nonita Sharma, Monika Mangla, Mohammed Ishaque, Sachi Nandan Mohanty
1st International Conference in Advanced Innovation on Smart City Icaisc 2023 Proceedings, 2023
Machine Learning Techniques for Aspect Analysis of Employee Attrition
Anamika Hooda, Purva Garg, Nonita Sharma, Monika Mangla
Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering Lnicst, 2023
An Artificial Intelligence and Computer Vision Based EyeWriter
Monika Mangla, Amaan Sayyad, Nonita Shama, Sachi Nandan Mohanty, Debabrata Singh
Smart Innovation Systems and Technologies, 2023
Footy Forecast - Measuring Performance in Football
Chirag Rohra, Monika Mangla, Shlok Asher, Neha Agarwal, Soham Desai
Proceedings of 3rd International Conference on Advanced Computing Technologies and Applications Icacta 2023, 2023
A sequential ensemble model for software fault prediction
Monika Mangla, Nonita Sharma, Sachi Nandan Mohanty
Innovations in Systems and Software Engineering, 2022
LSTM based decision support system for swing trading in stock market
Shouvik Banik, Nonita Sharma, Monika Mangla, Sachi Nandan Mohanty, Shitharth S.
Knowledge Based Systems, 2022
A Markov decision process-based secure consensus framework for leveraging blockchain technology in IoT applications
Nonita Sharma, Monika Mangla, Sachi Nandan Mohanty
International Journal of Electronic Business, 2022
Time Series Forecasting Techniques for Infectious Disease Prediction
Jaiditya Dev, Monika Mangla, Nonita Sharma, K. P. Sharma
Handbook of Research on Machine Learning Foundations and Applications, 2022
Analysis and Visualization of Heart Failure Prediction Dataset
Dhyani Patel, Sukanya Chopra, Nonita Sharma, Monika Mangla
Aist 2022 4th International Conference on Artificial Intelligence and Speech Technology, 2022
Analysis and Visualization of Netflix Shows
Devashree, Himanshi Goel, Nonita Sharma, Monika Mangla
Aist 2022 4th International Conference on Artificial Intelligence and Speech Technology, 2022
Employing Machine Learning for Predictive Data Analytics in Healthcare
Rakhi Akhare, Monika Mangla, Sanjivani Deokar, Hardik Deshmukh
Handbook of Research on Machine Learning Foundations and Applications, 2022
Aspect Analysis of Dementia Patients
Saloni Gupta, Riya Sharma, Nonita Sharma, Monika Mangla
2022 3rd International Conference on Issues and Challenges in Intelligent Computing Techniques Icict 2022, 2022
Uses And Challenges of Deep Learning Models for Covid-19 Diagnosis and Prediction
Vaishali M. Wadhwa, Monika Mangla, Rattandeep Aneja, Mukesh Chawla, Achyuth Sarkar
Challenges and Opportunities for Deep Learning, 2022
Regression Analysis & Visualization of Twitch Dataset
Insha Khan, Riya Kumari, Nonita Sharma, Monika Mangla, Inderdeep Kaur
2022 3rd International Conference on Issues and Challenges in Intelligent Computing Techniques Icict 2022, 2022
Handbook of Research on Machine Learning: Foundations and Applications
Monika Mangla, Subhash K. Shinde, Vaishali Mehta, Nonita Sharma, Sachi Nandan Mohanty
Handbook of Research on Machine Learning Foundations and Applications, 2022
PREFACE
Challenges and Opportunities for Deep Learning, 2022
Challenges and Opportunities for Deep Learning
Challenges and Opportunities for Deep Learning, 2022
A Proposed Framework to Achieve CIA in IoT Networks
Monika Mangla, Smita Ambarkar, Rakhi Akhare, Sanjivani Deokar, Sachi Nandan Mohanty, Suneeta Satpathy
Lecture Notes in Electrical Engineering, 2022
A sequential ensemble model for photovoltaic power forecasting
Nonita Sharma, Monika Mangla, Sourabh Yadav, Nitin Goyal, Aman Singh, Sahil Verma, Takfarinas Saber
Computers and Electrical Engineering, 2021
A Heterogeneous Ensemble Forecasting Model for Disease Prediction
Nonita Sharma, Jaiditya Dev, Monika Mangla, Vaishali Mehta Wadhwa, Sachi Nandan Mohanty, Deepti Kakkar
New Generation Computing, 2021
Employing stacked ensemble approach for time series forecasting
Nonita Sharma, Monika Mangla, Sachi Nandan Mohanty, Chinmaya Ranjan Pattanaik
International Journal of Information Technology Singapore, 2021
Security of sensitive data in cloud computing
Kirti Wanjale, Monika Mangla, Paritosh Marathe
Machine Learning Approach for Cloud Data Analytics in Iot, 2021
Employing machine learning approaches for predictive data analytics in retail industry
Rakhi Akhare, Sanjivani Deokar, Monika Mangla, Hardik Deshmukh
Machine Learning Approach for Cloud Data Analytics in Iot, 2021
Preface
Machine Learning Approach for Cloud Data Analytics in Iot, 2021
Machine learning approach for cloud data analytics in IoT
Machine Learning Approach for Cloud Data Analytics in Iot, 2021
Predicting mortality rate and associated risks in COVID-19 patients
Suneeta Satpathy, Monika Mangla, Nonita Sharma, Hardik Deshmukh, Sachinandan Mohanty
Spatial Information Research, 2021
A smart ontology-based IoT framework for remote patient monitoring
Nonita Sharma, Monika Mangla, Sachi Nandan Mohanty, Deepak Gupta, Prayag Tiwari, Mohammad Shorfuzzaman, Majdi Rawashdeh
Biomedical Signal Processing and Control, 2021
A fuzzy-based expert system to analyse purchase behaviour under uncertain environment
Doan Van Thang, Monika Mangla, Suneeta Satpathy, Chinmaya Ranjan Pattnaik, Sachi Nandan Mohanty
International Journal of Information Technology Singapore, 2021
An AI and Computer Vision-based Face Mask Recognition & Detection System
Monika Mangla, Amaan Sayyad, Sachi Nandan Mohanty
Icsccc 2021 International Conference on Secure Cyber Computing and Communications, 2021
An Analysis and Investigation of InfoStealers Attacks during COVID'19: A Case Study
Ravi Sharma, Nonita Sharma, Monika Mangla
Icsccc 2021 International Conference on Secure Cyber Computing and Communications, 2021
A gesture based remote control for home appliances
N. Sharma, M. Mangla, S. Mohanty, Suneeta Satpathy
Proceedings of the 2021 8th International Conference on Computing for Sustainable Global Development Indiacom 2021, 2021
A stochastic neighbor embedding approach for cancer prediction
Nonita Sharma, Monika Mangla, Sachi Nandan Mohanty, Suneeta Satpaty
2021 International Conference on Emerging Smart Computing and Informatics Esci 2021, 2021
A secure fog computing architecture for continuous health monitoring
Sanjivani Deokar, Monika Mangla, Rakhi Akhare
Signals and Communication Technology, 2021
A fuzzy expert system for predicting the mortality of COVID'19
Monika MANGLA, Nonita SHARMA, Poonam MITTAL
Turkish Journal of Electrical Engineering and Computer Sciences, 2021
Integration of Cloud Computing with Internet of Things: Foundations, Analytics, and Applications
Integration of Cloud Computing with Internet of Things Foundations Analytics and Applications, 2021
Blockchain and IPFS Based Framework for Secure Student Document Record Keeping
Journal of Educational Multimedia and Hypermedia, 2021
A Proposed Framework for Autonomic Resource Management in Cloud Computing Environment
Monika Mangla, Sanjivani Deokar, Rakhi Akhare, Mehdi Gheisari
Eai Springer Innovations in Communication and Computing, 2021
Statistical Analysis for Air Quality Assessment and Evaluation: A Data Mining Approach
Monika Mangla, Nonita Sharma, Vaishali Mehta, Sachi Nandan Mohanty, Komal Saxena
2021 9th International Conference on Reliability Infocom Technologies and Optimization Trends and Future Directions Icrito 2021, 2021
Multivariate economic analysis of the government policies and COVID-19 on financial sector
Monika Mangla, Nonita Sharma, Sourabh Yadav, Vaishali Mehta, Deepti Kakkar, Prabhakar Kandukuri
International Journal of Computer Applications in Technology, 2021
Preface
Emerging Technologies for Healthcare Internet of Things and Deep Learning Models, 2021
Emerging Technologies for Healthcare: Internet of Things and Deep Learning Models
Emerging Technologies for Healthcare Internet of Things and Deep Learning Models, 2021
An ensemble approach to forecast COVID-19 incidences using linear and non-linear statistical models
Asmita Mahajan, Nonita Sharma, Firas Husham Almukhtar, Monika Mangla, Krishna Pal Sharma, Rajneesh Rani
International Journal of Computer Applications in Technology, 2021
Detection and Prevention Mechanisms for DDoS Attack in Cloud Computing Environment
Sirisha Potluri, Monika Mangla, Suneeta Satpathy, Sachi Nandan Mohanty
2020 11th International Conference on Computing Communication and Networking Technologies Icccnt 2020, 2020
A Capacitated Facility Allocation Approach Based on Residue for Constrained Regions
Monika Mangla, Deepak Garg
Advances in Intelligent Systems and Computing, 2020
Employing Machine Learning for Multi-perspective Emotional Health Analysis
Monika Mangla, Rakhi Akhare, Sanjivani Deokar, Vaishali Mehta
Emotion and Information Processing A Practical Approach, 2020
Proposed Framework for Fog Computing to Improve Quality-of-Service in IoT Applications
Rakhi Akhare, Monika Mangla, Sanjivani Deokar, Vaishali Wadhwa
Studies in Big Data, 2020
Context-aware automation based energy conservation techniques for IoT ecosystem
Monika Mangla, Rakhi Akhare, Smita Ambarkar
Studies in Systems Decision and Control, 2019
Rapidly converging solution for p-centers in nonconvex regions
Monika MANGLA, Deepak GARG
Turkish Journal of Electrical Engineering and Computer Sciences, 2017
Exploiting OLAP and data mining for augmenting e-business
Monika Mangla
2009 International Conference on Intelligent Agent and Multi Agent Systems Iama 2009, 2009

Monika Mangla

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