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Rainfall Forecasting Using Machine Learning Algorithms for Localized Events

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Computers, Materials & Continua 2022年第6期71卷 6333-6350页

作者： Ganapathy Pattukandan Ganapathy kathiravan srinivasan Debajit Datta Chuan-Yu Chang Om Purohit Vladislav Zaalishvili Olga Burdzieva Centre for Disaster Mitigation and Management Vellore Institute of TechnologyVellore632014India School of Computer Science and Engineering Vellore Institute of TechnologyVellore632014India Department of Computer Science and Information Engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan Service Systems Technology Center Industrial Technology Research InstituteHsinchuTaiwan School of Information Technology and Engineering Vellore Institute of TechnologyVellore632014India Geophysical Institute of Vladikavkaz Scientific Centre Russian Academy of Sciences(RAS)VladikavkazRussian Federation

A substantial amount of the Indian economy depends solely on ***,on the other hand,plays a significant role in agriculture–while an adequate amount of rainfall can be considered as a blessing,if the amount is inordinate or scant,it can ruin the entire hard work of the *** this work,the rainfall dataset of the Vellore region,of Tamil Nadu,India,in the years 2021 and 2022 is forecasted using several machine learning *** engineering has been performed in this work in order to generate new features that remove all sorts of autocorrelation present in the *** removal of autocorrelation,the data could be used for performing operations on the time-series data,which otherwise could only be performed on any other regular regression *** work uses forecasting techniques like the AutoRegessive Integrated Moving Average(ARIMA)and exponential smoothening,and then the time-series data is further worked on using Long Short Term Memory(LSTM).Later,regression techniques are used by manipulating the *** work is benchmarked with several evaluation metrics on a test dataset,where XGBoost Regression technique outperformed the *** uniqueness of this work is that it forecasts the daily rainfall for the year 2021 and 2022 in Vellore *** work can be extended in the future to predict rainfall over a bigger region based on previously recorded time-series data,which can help the farmers and common people to plan accordingly and take precautionary measures.

关键词： Time-series ARIMA LSTM regression rainfall

Early Tumor Diagnosis in Brain MR Images via Deep Convolutional Neural Network Model

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Computers, Materials & Continua 2021年第8期68卷 2413-2429页

作者： Tapan Kumar Das Pradeep Kumar Roy Mohy Uddin kathiravan srinivasan Chuan-Yu Chang Shabbir Syed-Abdul School of Information Technology and Engineering Vellore Institute of TechnologyVellore632014India Department of Computer Science and Engineering Indian Institute of Information TechnologySurat395007India Research Quality Management Section King Abdullah International Medical Research CenterKing Saud bin Abdulaziz University for Health SciencesMinistry of National Guard-Health AffairsRiyadh11426Kingdom of Saudi Arabia Department of Computer Science and Information Engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan Graduate Institute of Biomedical Informatics Taipei Medical UniversityTaipeiTaiwan

Machine learning based image analysis for predicting and diagnosing certain diseases has been entirely trustworthy and even as efficient as a domain expert’s ***,the style of non-transparency functioning by a trained machine learning system poses a more significant impediment for seamless knowledge trajectory,clinical mapping,and delusion *** this proposed study,a deep learning based framework that employs deep convolution neural network(Deep-CNN),by utilizing both clinical presentations and conventional magnetic resonance imaging(MRI)investigations,for diagnosing tumors is *** research aims to develop a model that can be used for abnormality detection over MRI data quite efficiently with high *** research is based on deep learning and Deep-CNN was deployed to examine the MR brain image for tracing the *** system runs on Tensor flow and uses a feature extraction module in DeepCNN to elicit the factors of that part of the image from where underlying issues are identified and subsequently succeeded in prediction of the disease in the MR *** results of this study showed that our model did not have any adverse effect on classification,achieved higher accuracy than the peers in recent years,and attained good detection outcomes including case of *** the future work,further improvement can be made by designing models that can drastically reduce the parameter space without affecting classification accuracy.

关键词： Deep learning convolutional neural network brain tumor magnetic resonance imaging

Eye Gaze Detection Based on Computational Visual Perception and Facial Landmarks

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Computers, Materials & Continua 2021年第8期68卷 2545-2561页

作者： Debajit Datta Pramod Kumar Maurya kathiravan srinivasan Chuan-Yu Chang Rishav Agarwal Ishita Tuteja V.Bhavyashri Vedula School of Computer Science and Engineering Vellore Institute of Technology(VIT)Vellore632014India School of Information Technology and Engineering Vellore Institute of Technology(VIT)Vellore632014India Department of Computer Science and Information Engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan

The pandemic situation in 2020 brought about a‘digitized new normal’and created various issues within the current education *** of the issues is the monitoring of students during online examination situations.A system to determine the student’s eye gazes during an examination can help to eradicate *** this work,we track the users’eye gazes by incorporating twelve facial landmarks around both eyes in conjunction with computer vision and the HAAR *** aim to implement eye gaze detection by considering facial landmarks with two different Convolutional Neural Network(CNN)models,namely the AlexNet model and the VGG16 *** proposed system outperforms the traditional eye gaze detection system which only uses computer vision and the HAAR classifier in several evaluation metric *** proposed system is accurate without the need for complex ***,it can be implemented in educational institutes for the fair conduct of examinations,as well as in other instances where eye gaze detection is required.

关键词： Computer vision convolutional neural network data integrity digital examination eye gaze detection extraction information entropy

Performance Comparison of Deep CNN Models for Detecting Driver’s Distraction

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Computers, Materials & Continua 2021年第9期68卷 4109-4124页

作者： kathiravan srinivasan Lalit Garg Debajit Datta Abdulellah A.Alaboudi N.Z.Jhanjhi Rishav Agarwal Anmol George Thomas School of Information Technology and Engineering Vellore Institute of TechnologyVellore632014India Faculty of Information and Communication Technology University of MaltaMsida2080MSDMalta School of Computer Science and Engineering Vellore Institute of TechnologyVellore632014India College of Computer Science Shaqra UniversityKingdom of Saudi Arabia School of Computer Science and Engineering SCETaylor’s UniversitySubang Jaya47500Malaysia

According to various worldwide statistics,most car accidents occur solely due to human *** person driving a car needs to be alert,especially when travelling through high traffic volumes that permit high-speed transit since a slight distraction can cause a fatal *** though semiautomated checks,such as speed detecting cameras and speed barriers,are deployed,controlling human errors is an arduous *** key causes of driver’s distraction include drunken driving,conversing with co-passengers,fatigue,and operating gadgets while *** these distractions are accurately predicted,the drivers can be alerted through an alarm ***,this research develops a deep convolutional neural network(deep CNN)models for predicting the reason behind the driver’s *** deep CNN models are trained using numerous images of distracted *** performance of deep CNN models,namely the VGG16,ResNet,and Xception network,is assessed based on the evaluation metrics,such as the precision score,the recall/sensitivity score,the F1 score,and the specificity *** ResNet model outperformed all other models as the best detection model for predicting and accurately determining the drivers’activities.

关键词： Deep-CNN ResNet Xception VGG16 data classification

Fuzzy Logic-Based Health Monitoring System for COVID’19 Patients

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Computers, Materials & Continua 2021年第5期67卷 2431-2447页

作者： M.Jayalakshmi Lalit Garg K.Maharajan K.Jayakumar kathiravan srinivasan Ali Kashif Bashir K.Ramesh National Engineering College Kovilpatti628503India Faculty of Information and Communication Technology University of MaltaMsidaMSD2080Malta Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai600062India School of Computer Science and Engineering Vellore Institute of Technology(VIT)Vellore632014India School of Information Technology and Engineering Vellore Institute of Technology(VIT)Vellore632014India Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUK Department of Computer Science Karnataka State Akkamahadevi Women’s UniversityVijayapuraIndia

In several countries,the ageing population contour focuses on high healthcare costs and overloaded health care *** health care monitoring system can be a potential alternative,especially in the COVID-19 pandemic situation to help mitigate such problems by encouraging healthcare to transition from hospital-centred services to self-care,mobile care and home *** this aspect,we propose a pervasive system to monitor the COVID’19 patient’s conditions within the hospital and outside by monitoring their medical and psychological *** facilitates better healthcare assistance,especially for COVID’19 patients and quarantined *** identies the patient’s medical and psychological condition based on the current context and activities using a fuzzy context-aware reasoning engine based *** reasoning engine makes decisions using linguistic rules based on inference mechanisms that support the patient condition *** rules are framed based on the fuzzy set attributes belong to different context *** fuzzy semantic rules are used to identify the relationship among the attributes,and the reasoning engine is used to ensure precise real-time context interpretation and current evaluation of the *** are measured using a fuzzy logic-based context reasoning system under *** results indicate the usefulness of monitoring the COVID’19 patients based on the current context.

关键词： Pervasive healthcare COVID’19 context-aware fuzzy reasoning engine fuzzy logic role-based expert system

A Contemporary Review on Drought Modeling Using Machine Learning Approaches

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Computer Modeling in Engineering & Sciences 2021年第8期128卷 447-487页

作者： Karpagam Sundararajan Lalit Garg kathiravan srinivasan Ali Kashif Bashir Jayakumar Kaliappan Ganapathy Pattukandan Ganapathy Senthil Kumaran Selvaraj T.Meena School of Information Technology and Engineering Vellore Institute of TechnologyVellore632014India Faculty of Information and Communication Technology University of MaltaMsidaMSD2080Malta Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterM156BHUK School of Computer Science and Engineering Vellore Institute of TechnologyVellore632014India Centre for Disaster Mitigation and Management Vellore Institute of TechnologyVellore632014India Department of Manufacturing Engineering School of Mechanical EngineeringVellore Institute of TechnologyVellore632014India School of Civil Engineering Vellore Institute of TechnologyVellore632014India

Drought is the least understood natural disaster due to the complex relationship of multiple contributory factors. Itsbeginning and end are hard to gauge, and they can last for months or even for years. India has faced many droughtsin the last few decades. Predicting future droughts is vital for framing drought management plans to sustainnatural resources. The data-driven modelling for forecasting the metrological time series prediction is becomingmore powerful and flexible with computational intelligence techniques. Machine learning (ML) techniques havedemonstrated success in the drought prediction process and are becoming popular to predict the weather, especiallythe minimum temperature using backpropagation algorithms. The favourite ML techniques for weather forecastinginclude support vector machines (SVM), support vector regression, random forest, decision tree, logistic regression,Naive Bayes, linear regression, gradient boosting tree, k-nearest neighbours (KNN), the adaptive neuro-fuzzyinference system, the feed-forward neural networks, Markovian chain, Bayesian network, hidden Markov models,and autoregressive moving averages, evolutionary algorithms, deep learning and many more. This paper presentsa recent review of the literature using ML in drought prediction, the drought indices, dataset, and performancemetrics.

关键词： Drought forecasting machine learning drought indices stochastic models fuzzy logic dynamic method hybrid method

An Efficient Sound and Data Steganography Based Secure Authentication System

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Computers, Materials & Continua 2021年第4期67卷 723-751页

作者： Debajit Datta Lalit Garg kathiravan srinivasan Atsushi Inoue G.Thippa Reddy M.Praveen Kumar Reddy K.Ramesh Nidal Nasser School of Computer Science and Engineering Vellore Institute of Technology(VIT)Vellore632014India Faculty of Information and Communication Technology University of MaltaMsidaMSD2080Malta School of Information Technology and Engineering Vellore Institute of Technology(VIT)Vellore632014India Department of Information Systems&Business Analytics Eastern Washington UniversitySpokaneWA99202USA Department of Computer Science Karnataka State Akkamahadevi Women’s UniversityVijayapuraIndia College of Engineering Alfaisal UniversityRiyadh1153Saudi Arabia

The prodigious advancements in contemporary technologies have also brought in the situation of unprecedented ***,the pin-based security system is an inadequate mechanism for handling such a *** reason is that hackers use multiple strategies for evading security systems and thereby gaining access to private *** research proposes to deploy diverse approaches for authenticating and securing a connection amongst two devices/gadgets via sound,thereby disregarding the pins’manual ***,the results demonstrate that the proposed approaches outperform conventional pin-based authentication or QR authentication ***,a random signal is encrypted,and then it is transformed into a wave file,after which it gets transmitted in a short burst via the device’s ***,the other device/gadget captures these audio bursts through its microphone and decrypts the audio signal for getting the essential data for ***,this model requires two devices/gadgets with speakers and a microphone,and no extra hardware such as a camera,for reading the QR code is *** first module is tested with realtime data and generates high scores for the widely accepted accuracy metrics,including precision,Recall,F1 score,entropy,and mutual information(MI).Additionally,this work also proposes a module helps in a secured transmission of sensitive data by encrypting it over images and other *** steganographic module includes two-stage encryption with two different encryption algorithms to transmit data by embedding inside a *** encryption algorithms and their combinations are taken for this system to compare the resultant file *** these systems engender high accuracies and provide secure connectivity,leading to a sustainable communication ecosystem.

关键词： Cyber-attacks signals privacy security organization encryption decryption authentication effective communication steganography

The Synergy of Combined Use of DMSO and Bronsted Acid (Ionic Liquid) as a Catalyst Part I: Efficient Niementowski Synthesis of Modified Quinazolinones

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Green and Sustainable Chemistry 2011年第1期1卷 12-18页

作者： Muthu K. kathiravan Rajeshwar R. Jalnapurkar Trupti S. Chitre Riyaj S. Tamboli Kumar V. srinivasan 不详

A new rapid and versatile approach using Ionic liquid/DMSO as a chemical reagent for the synthesis of fused heterocyclic compounds in a highly efficient way is described. This method offers the advantages of proceeding in neutral conditions, giving high to excellent isolated yields (83–92%) for Niementowski synthesis with easy workup procedure. The inherent Bronsted acidity of ionic liquid and high polarity of both IL and DMSO resulted in a significant enhancement in the reaction rate.

关键词： Ionic Liquids DMSO Niementowski