Dr. Meenu Gupta - Academia.edu (original) (raw)

Papers by Dr. Meenu Gupta

Endocrine

Background An unhealthy diet or excessive amount of food intake creates obesity issues in human b... more Background An unhealthy diet or excessive amount of food intake creates obesity issues in human beings that further may cause several diseases such as Polycystic Ovary Syndrome (PCOS), Cardiovascular disease, Diabetes, Cancers, etc. Obesity is a major risk factor for PCOS, which is a common disease in women and is significantly correlated with weight gain. Methods This study is providing a one-step solution for predicting the risk of obesity using different Machine Learning (ML) algorithms such as Gradient Boosting (GB), Bagging meta-estimator (BME), XG Boost (XGB), Random Forest (RF), Support Vector Machine (SVM), and K Nearest Neighbour (KNN). A dataset is collected from the UCI ML repository having features of physical description and eating habits of individuals to train the proposed model. Results The model has been experimented with different training and testing data ratios such as (90:10, 80:20, 70:30,60:40). At a data ratio of 90:10, the GB classifier achieved the highest accuracy i.e., 98.11%. Further, at the 80:20 ratio, the GB and XGB provide the same result i.e., 97.87%. For the 70:30 data ratio, XGB achieves the highest accuracy i.e., 97.79%. Further, the Nearest Neighbour (NN) learning method is applied to meal planning to overcome obesity. Conclusion This method predicts the meal which includes breakfast, morning snacks, lunch, evening snacks, and dinner for the individual as per caloric and macronutrient requirements. The proposed research work can be used by practitioners to check obesity levels and to suggest meals to reduce the obese in adulthood.

Acta Universitatis Sapientiae, Informatica

Automatic bokeh is one of the smartphone’s essential photography effects. This effect enhances th... more Automatic bokeh is one of the smartphone’s essential photography effects. This effect enhances the quality of the image where the subject background gets out of focus by providing a soft (i.e., diverse) background. Most smartphones have a single rear camera that is lacking to provide which effects need to be applied to which kind of images. To do the same, smartphones depend on different software to generate the bokeh effect on images. Blur, Color-point, Zoom, Spin, Big Bokeh, Color Picker, Low-key, High-Key, and Silhouette are the popular bokeh effects. With this wide range of bokeh types available, it is difficult for the user to choose a suitable effect for their images. Deep Learning (DL) models (i.e., MobileNetV2, InceptionV3, and VGG16) are used in this work to recommend high-quality bokeh effects for images. Four thousand five hundred images are collected from online resources such as Google images, Unsplash, and Kaggle to examine the model performance. 85% accuracy has been ...

2022 Fifth International Conference on Computational Intelligence and Communication Technologies (CCICT)

2021 International Conference in Advances in Power, Signal, and Information Technology (APSIT), 2021

Breast cancer is one of the woman's most prominent cancer and most malignant of all cancers. ... more Breast cancer is one of the woman's most prominent cancer and most malignant of all cancers. It is the world's largest autopsy of cancer deaths for females and happens in about 3 from 10 people. This article includes numerous machine learning methods and data mining strategies to assess the early detection of breast cancer. Machine learning is used in clinical applications such as identification of cancer cells. The cancerous cells are categorized as Benign and Malignant. This paper analyzes the quality of numerous unsupervised, supervised and other methods for the integrity and prediction for breast cancer. This research could provide various methodologies to better understand early cancer detection. Early detection for breast cancer can be a potential benefit in the management of this condition, not only does early treatment make it possible to heal it, but it also prevent its recurrence.

Web Services, 2019

Data can be anything but from a large data base extraction of useful information is known as data... more Data can be anything but from a large data base extraction of useful information is known as data mining. Cloud computing is a term which represent a collection of huge amount of data. Cloud computing can be correlated with data mining and Big Data Hadoop. Big data is high volume, high velocity, and/or high variety information asset that require new form of processing to enable enhanced decision making, insight discovery and process optimization. Data growth, speed and complexity are being accompanied by deployment of smart sensors and devices that transmit data commonly called the Internet of Things, multimedia and by other sources of semi-structured and structured data. Big Data is defined as the core element of nearly every digital transformation today.

Computational Analysis and Deep Learning for Medical Care, 2021

Digital Twin Technology, 2021

An important application of speech processing is speaker recognition, which automatically recogni... more An important application of speech processing is speaker recognition, which automatically recognizes the person speaking in an audio recording, basis of which is speaker-specific information included in its speech features. It involves speaker verification and speaker identification. This paper presents an efficient method based on discrete wavelet transform and optimized variance spectral flux to enhance the enactment of speaker identification system. An effective feature extraction technique uses Daubechies 40 (db40) wavelet to compress and de-noised the speech signal by its decomposition into approximations and details coefficients at level 1. The approximation coefficients contain 99.9% of speech information as compared to detailed coefficients. So, the optimized variance spectral flux is applied on wavelet approximation coefficients which efficiently extract the frequency contents of the speech signal and gives unique features. The distance between extracted features has been o...

Studies in Systems, Decision and Control, 2021

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. The ... more Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. The disease causes a respiratory illness with symptoms like cough and fever and, in more severe cases, causes difficulty while breathing. COVID-19 spreads primarily through contact with an infected person when they sneeze or cough or by touching a surface that has that virus on it and then touching our mouth, nose, or eyes. The disease was first observed in the central Chinese city of Wuhan at the end of 2019. The outbreak has been declared a global pandemic. The novel coronavirus is already reorienting our lives, but the crisis moments also present an opportunity for more sophisticated and flexible use of technology. The epidemic is impacting the global population as the number of cases is increasing rapidly, and there is an urgent need to stop the virus from spreading. The outbreak has triggered massive demand for digital health solutions, and for this, the drones and robots present an excellent method for automation of manual activities. Drones and robots can be used to provide services to the patients and those who are quarantined and are the most desirable and safe way to fight against the outbreak and limit contamination and spread of the virus. The following chapter will discuss the various solutions based on drones and robots in the field of AI and IoT, such as drones being used for social distancing and robots for sanitization. Further, analysis has been made about the total number of cases and deaths around the world and also how it has affected humanity and what measures have been taken to control this deadly disease.

Intelligent Automation & Soft Computing, 2022

Hearing a species in a tropical rainforest is much easier than seeing them. If someone is in the ... more Hearing a species in a tropical rainforest is much easier than seeing them. If someone is in the forest, he might not be able to look around and see every type of bird and frog that are there but they can be heard. A forest ranger might know what to do in these situations and he/she might be an expert in recognizing the different type of insects and dangerous species that are out there in the forest but if a common person travels to a rain forest for an adventure, he might not even know how to recognize these species, let alone taking suitable action against them. In this work, a model is built that can take audio signal as input, perform intelligent signal processing for extracting features and patterns, and output which type of species is present in the audio signal. The model works end to end and can work on raw input and a pipeline is also created to perform all the preprocessing steps on the raw input. In this work, different types of neural network architectures based on Long Short Term Memory (LSTM) and Convolution Neural Network (CNN) are tested. Both are showing reliable performance, CNN shows an accuracy of 95.62% and Log Loss of 0.21 while LSTM shows an accuracy of 93.12% and Log Loss of 0.17. Based on these results, it is shown that CNN performs better than LSTM in terms of accuracy while LSTM performs better than CNN in terms of Log Loss. Further, both of these models are combined to achieve high accuracy and low Log Loss. A combination of both LSTM and CNN shows an accuracy of 97.12% and a Log Loss of 0.16.

Big Data Analysis for Green Computing, 2021

Ingeniería Solidaria, 2017

Introduction: Traffic accidents are an undesirable burden on society. Every year around one milli... more Introduction: Traffic accidents are an undesirable burden on society. Every year around one million deaths and more than ten million injuries are reported due to traffic accidents. Hence, traffic accidents prevention measures must be taken to overcome the accident rate. Different countries have different geographical and environmental conditions and hence the accident factors diverge in each country. Traffic accident data analysis is very useful in revealing the factors that affect the accidents in different countries. This article was written in the year 2016 in the Institute of Technology & Science, Mohan Nagar, Ghaziabad, up, India. Methology: We propose a framework to utilize association rule mining (arm) for the severity classification of traffic accidents data obtained from police records in Mujjafarnagar district, Uttarpradesh, India. Results: The results certainly reveal some hidden factors which can be applied to understand the factors behind road accidentality in this regi...

This paper analyses the network security issues and threats which are increasing every day. Data ... more This paper analyses the network security issues and threats which are increasing every day. Data centre operators, network administrator, and other data centre professionals need to comprehend the basics of security in order to safely deploy and manage networks today. Because of network and threats issue and different solutions to solve this problem this paper basically analyses about the implementation of firewall and IDS. It synthesizes the firewall and intrusion detection techniques which are being used. It explains different type of detection and prevention systems which are used for securing the network from the attacks. Main objective of this paper is to case study, analyses on network and features of pfSense and how to implement it. pfSense offers different solutions,easy rule management, Blacklisting, NAT, VPN and package system that allows to expand its services.

Handbook of IoT and Big Data, 2019

Fusion: Practice and Applications, 2021

Bitcoin is one of the primary computerized monetary forms to utilize peer innovation to work with... more Bitcoin is one of the primary computerized monetary forms to utilize peer innovation to work with moment installments. The free people and organizations who own the overseeing figuring control and take part in the bitcoin network—bitcoin miners— are accountable for preparing the exchanges on the blockchain and are persuaded by remunerations (the arrival of new bitcoin) and exchange charges paid in bitcoin. These excavators can be considered as the decentralized authority implementing the believability of the bitcoin network. New bitcoin is delivered to the excavators at a fixed yet occasionally declining rate. There is just 21 million bitcoin that can be mine altogether. As of January 30, 2021, there are around 18,614,806 bitcoin in presence and 2,385,193 bitcoin left to be mined. This paper will predict the nature of bitcoin price because, according to the reports of the past few years. The year 2020-present appeared to be a good time for bitcoin because, in this time duration, bit...

The Data mining projects are complex and can have a high failure rate. In order to improve projec... more The Data mining projects are complex and can have a high failure rate. In order to improve project management and success rates of such projects a life cycle is very important to the overall success of the project. This paper is concerned with the life cycle development for data mining projects. The paper provides a detailed view of the design and development of the data mining life cycle called DMLC. The life cycle aims to support all members of data mining project teams as well as IT managers and academic researchers and may improve project success rates and strategic decision support. An extensive analysis of life cycle leads to a list of advantages, disadvantages, and characteristics of the life cycle. This is extended and generates a corporation of several guidelines which serve as the foundation for the development of a new generic data mining life cycle.

2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), 2016

Intrusions are generally refereed as an attempt to bypass of security policy of the computer syst... more Intrusions are generally refereed as an attempt to bypass of security policy of the computer systems or networks, i.e., the violation of security policies of computer systems. Indeed, such attempt on computer systems may give rise to serious disasters with high economic impacts on IT-infrastructure. In this paper, the two most serious intrusions in the cloud, namely, “Insider attack” and “Flooding attack” are considered for the discussion. The various existing survey report, characteristics of these two intrusions and techniques used to provide defense against these threats are highlighted. It has been revealed that none of the existing solution is sufficient to provide strong defense against these intrusions. Finally, few solutions for strong defense, especially, from insider attack, are suggested.