Vinayakumar Ravi

Vinayakumar Ravi
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Vinayakumar verified their affiliation via an institutional email.
Prince Mohammad bin Fahd University · Center for Artificial Intelligence

Assistant Research Professor
Researching, & developing novel machine/deep learning algorithms and applications for Biomedical and Cyber Security.

About

430
Publications
319,797
Reads
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11,890
Citations
Introduction
I am an Assistant Research Professor in Center for Artificial Intelligence at Prince Mohammad Bin Fahd University. I am working in the area of artificial intelligence, machine learning, deep learning, and natural language processing for Biomedicine and Cyber Security. My work includes researching, developing and implementing novel computational and machine learning algorithms and applications for big data integration and data mining. More details available at https://vinayakumarr.github.io/
Additional affiliations
September 2019 - August 2020
Cincinnati Children's Hospital Medical Center
Position
  • Research Associate
Description
  • Researching, developing and implementing novel computational and machine learning algorithms and applications for big data integration and data mining.
June 2019 - September 2019
Amrita Vishwa Vidyapeetham
Position
  • Research Associate
Description
  • Developing machine learning based cyber security and bioinformatics
January 2014 - June 2015
Amrita Vishwa Vidyapeetham
Position
  • Research Assistant
Description
  • Development of computational thinking tools
Education
June 2015 - June 2019
Amrita Vishwa Vidyapeetham
Field of study
  • Machine Learning, Data mining and Deep learning, Big Data Analytics, Natural language processing, Signal and Image processing and Casual inference for Cyber Security

Publications

Publications (430)
Article
With the rapid advancements in artificial intelligence (AI), ensuring the privacy and security of patient medical images has emerged as a pressing concern in the field of image privacy protection. Traditional medical image encryption methods, however, have often been criticized for their lack of flexibility and insufficient security measures. To ad...
Article
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Edge Computing (EC) is a revolutionary architecture that brings Cloud Computing (CC) services closer to data sources than ever before. This research proposed novel technique in edge computing network based on wireless 5G technology using MIMO_federated learning integrated with Reinforcement neural network. Here the aim is to enhance the resource al...
Cover Page
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Abstract Submission: March 10 Abstract Acceptance: March 20 Full Chapter Submission: May 25 Chapter Review: June 25 Revised chapter submission: July 15 Final chapter acceptance: Aug 15 Final chapter submission: Aug 22
Chapter
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Estimating cargo power is vital because it allows for efficient planning and optimization of transportation logistics, ensuring the appropriate allocation of resources and maximizing operational effectiveness. It also facilitates the assessment and mitigation of the environmental impact of transportation by optimizing fuel consumption and reducing...
Chapter
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Time series data, prevalent in diverse domains, reflects underlying dynamic processes crucial for informed decision-making. Our research marks a modest stride in comprehending these dynamics. In the context of disease surveillance, Time series forecasting and early warning indicators allow us to anticipate plausible infection waves and their severi...
Chapter
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The large-scale evolution of Internet and devices connected to the internet have led to various companies and organizations to protect their data on the internet to implement large scale IoT networks such as IIoT in the industrial point of view. Such large-scale networks need to be protected from malicious attacks. This makes it crucial for the nee...
Chapter
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Doctors can effectively manage patients’ treatments and diseases by leveraging advanced medical imaging, which significantly minimizes guesswork and enhances diagnoses and treatments.The use of Deep Learning (DL) has been increasing recently in the area of medical imaging for various diseases like Parkinson’s, Alzheimer’s, Blood Cancer etc. When it...
Article
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Nowadays, the digitalization boom witnesses the culmination of the Internet of Things (IoT), the big data and the cloud storage which is further fueled by data analytics techniques to identify useful patterns from the data stored in the cloud to understand the business and the government processes alike. In this competitive scenario, it is equally...
Article
Aim To address the vulnerability of Multi-Hop Wireless Network Systems (MHWNs) to jamming attacks and propose an effective solution to maintain communication integrity and Quality of Service (QoS). Background In MHWNs, the open-access nature makes them susceptible to jamming attacks, which disrupt communication by interfering with authenticated no...
Article
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Aims The aim of this research work is to compare the accuracy and precision of manual landmark identification versus automated methods using deep learning neural networks. Background Cephalometric landmark detection is a critical task in orthodontics and maxillofacial surgery and accurate identification of landmarks is essential for treatment plan...
Article
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INTRODUCTION: In integrating Spiral Coverage into Cellular Decomposition, which combines structured grid-based techniques with flexible, quick spiral traversal, time efficiency is increased.OBJECTIVES: In the field of robotics and computational geometry, the study proposes a comparative exploration of two prominent path planning methodologies—Boust...
Article
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Introduction Mucormycosis (black fungal attack) has recently been identified as a significant threat, specifically to patients who have recovered from coronavirus infection. This fungus enters the body through the nose and first infects the lungs but can affect other body parts, such as the eye and brain, resulting in vision loss and death. Early d...
Article
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Tomato (biological name: Solanum lycopersicum ) is an important food crop worldwide. However, due to climatic changes and various diseases, the yield of tomatoes decreased significantly, being detrimental from an economic point of view. Various diseases infect the tomato leaves, such as bacterial and septorial leaf spots, early blight and mosaic vi...
Article
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Background: In this article, the Mixed Mode Database Miner (MMDBM) algorithm is introduced for the classification of data. This algorithm depends on the decision tree classifier, which handles the numerical and categorical attributes. For the experimental analysis in a well-explored heart disease data set collected from the UCI Repository. Aims: Un...
Article
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Background The main emphasis of this study is on the medical Computed Tomography (CT) imaging denoising technique, which plays a major role in interpreting patient illness information for medical diagnosis. CT imaging is indispensable for accurate disease diagnosis, but image quality is affected by noise and other artifacts. The primary objective i...
Article
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Aims: The aim of this study is to develop a strong Multi-objective Convolutional Neural Network (MOCNN) optimized using Perceptual Pigeon Galvanized Optimization (PPGO) for accurate identification and classification of mango leaf diseases. This approach aims to increase classification accuracy, computational efficiency, and generalization ability....
Article
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Purpose The purpose of region-based medical image compression is to optimize the compression process by focusing on specific regions of interest within medical images. Unlike traditional compression methods that treat the entire image uniformly, region-based compression techniques identify and prioritize certain areas or regions within the image th...
Article
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Introduction Wildfires are an unexpected global hazard that significantly impact environmental change. An accurate and affordable method of identifying and monitoring on wildfire areas is to use coarse spatial resolution sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS)....
Article
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Introduction This research focuses on the concept of integrating Radial Basis Function Networks with deep learning models to solve robust regression tasks in both transportation and logistics. Methods It examines such combined models as RNNs with RBFNs, Attention Mechanisms with Radial Basis Function Networks (RBFNs), and Capsule Networks with RBF...
Chapter
The act of conveying thoughts and ideas to another person without using words or visible facial expressions is known as communication. It is a vital component of human existence since it enables interaction with the outside world. An audiovisual speech recognition system that uses image processing to aid speech recognition systems in the lip-readin...
Chapter
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Individuals and organizations use electronic mail (E-mail) to send and receive digital messages over the internet. In 2023, 347.3 billion emails are sent and received per day among which are spam emails. These emails can lead to communication overload, waste of time, irritation, loss of important emails, and potential exposure to malware. Irrelevan...
Chapter
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Segmenting medical images is crucial for clinical diagnosis and case analysis. Currently, most of the successful techniques are based on U-shaped encode and decoder-based convolutional neural networks (CNNs). A major drawback of these approaches is their limited capacity to establish highly relevant pattern connections and comprehensive contextual...
Preprint
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Ultrasound fetal imaging is beneficial to support prenatal development because it is affordable and non-intrusive. Nevertheless, fetal plane classification (FPC) remains challenging and time-consuming for obstetricians since it depends on nuanced clinical aspects, which increases the difficulty in identifying relevant features of the fetal anatomy....
Article
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Diabetic foot ulcers (DFUs) present a substantial health risk across diverse age groups, creating challenges for healthcare professionals in the accurate classification and grading. DFU plays a crucial role in automated health monitoring and diagnosis systems, where the integration of medical imaging, computer vision, statistical analysis, and gait...
Article
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Aim This study aims to enhance safety in large diameter tunnel construction by integrating robust optimization and machine learning (ML) techniques with Building Information Modeling (BIM). By acquiring and preprocessing various datasets, implementing feature engineering, and using algorithms like SVM, decision trees, ANN, and random forests, the s...
Article
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Aims: This research paper aims to check the effectiveness of a variety of machine learning models in classifying esophageal cancer through MRI scans. The current study encompasses Convolutional Neural Network (CNN), K-Nearest Neighbor (KNN), Recurrent Neural Network (RNN), and Visual Geometry Group 16 (VGG16), among others which are elaborated in t...
Article
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Aims This research seeks to improve the reliability and sustainability of tunnel construction by employing automated AI techniques to manage geotechnical and aleatoric uncertainties. It utilizes machine learning models, including Gradient Boosting Machines (GBM), AdaBoost, Hidden Markov Models (HMM), and Deep Q-Networks for Reinforcement Learning,...
Article
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Background Kidney stones, common urological diseases worldwide, are formed from hard urine minerals in the kidneys. Early detection is essential to prevent kidney damage and manage recurring stones. CT imaging has made significant progress in providing detailed information for disease diagnosis. Aim This study aimed to enhance kidney stone detecti...
Article
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Aim This research work aimed to combine different AI methods to create a modular diagnosis system for lung cancer, including Convolutional Neural Network (CNN), K-Nearest Neighbors (KNN), VGG16, and Recurrent Neural Network (RNN) on MRI biomarkers. Models have then been evaluated and compared in their effectiveness in detecting cancer, using a meti...
Article
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Visually, the environment is made up of a chaotic of irregular polygons. It is an important and intriguing issue in many fields of study to represent and comprehend the irregular polygon. However, approximating the polygon presents significant difficulties from a variety of perspectives. The method provided in this research eliminates the pseudo-re...
Research
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Call for Book Chapter, Springer (Scopus indexed)
Research
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Call for Book chapter, Elsevier (Scopus indexed)
Article
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Aims This study will investigate the integration of quantum computing and blockchain technology of EHR systems, evaluating the potential and major vulnerabilities of the developed blockchain platforms. In addition, through this evaluation, in this paper, transaction capabilities, energy consumption, and quantum susceptibilities of Ethereum, Bitcoin...
Article
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Disease spread is necessary to be controlled so that there is a chance to increase the survival rate of the people in particular zones. The outbreak of SARS-CoV-2 presents critical challenges exacerbated by atmospheric conditions and high population density. Existing time series methodologies for disease outbreak prediction lack spatial detail, hin...
Article
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Introduction In the 21 st century, human community witnessed a range of biological crises resulting in long-term consequences like loss of life, economic decline, trauma and social disruptions. COVID -19, named the SARs-CoV-2 virus by United Nations, was a similar outbreak in China in the year 2019, which later spread across the world. During the p...
Preprint
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Skin diseases affect over a third of the global population, yet their impact is often underestimated. Automating skin disease classification to assist doctors with their prognosis might be difficult. Nevertheless, due to efficient feature extraction pipelines, deep learning techniques have shown much promise for various tasks, including dermatologi...
Article
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Automated face recognition plays a vital role in forensics. The most important evidence in the criminal investigation is the facial images captured from the crime scene, as they represent the identity of the people involved in crime. The role of law enforcement agencies is to identify the facial images from the suitable database. This information c...
Article
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Aims Agriculture is one of the fundamental elements of human civilization. Crops and plant leaves are susceptible to many illnesses when grown for agricultural purposes. There may be less possibility of further harm to the plants if the illnesses are identified and classified accurately and early on. Background Plant leaf diseases are typically pr...
Article
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Aim This study aims to enhance the precision of Alzheimer's disease (AD) detection by integrating Spatial Attention Mechanism into a Convolutional Neural Network (CNN) architecture. Background Alzheimer's disease is a progressive neurodegenerative disorder characterized by abnormal protein deposits in the brain, leading to nerve cell loss and posi...
Article
Introduction: The thyroid is an endocrine gland located in the front of the neck whose main purpose is to produce thyroid hormones necessary for the functioning of the entire body. Thyroid hormones may be produced too little or too much depending on dysfunction. Since the 1990s, there have been an increasing number of thyroid illness cases, and in...
Article
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Introduction The thyroid is an endocrine gland located in the front of the neck whose main purpose is to produce thyroid hormones necessary for the functioning of the entire body. Thyroid hormones may be produced too little or too much depending on dysfunction. Since the 1990s, there have been an increasing number of thyroid illness cases, and in r...
Article
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Introduction The three prevalent yet detrimental respiratory conditions, namely COVID-19, pneumonia, and tuberculosis, exhibit overlapping symptoms, making their differentiation challenging. However, their treatments are significantly divergent. Early detection emerges as a critical common factor for the effective management of these diseases. The...
Article
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Radio frequency (RF) energy harvesting (EH) for wireless networks provides a green and sustainable solution and offers an energy‐efficient system. It is most crucial for fulfilling the power requirement of the rising number of low‐powered wireless devices and achieving sustainable development goals (SDG). It ensures the longevity of devices in the...
Chapter
A cybersecurity paradigm known as “zero trust” is centred on resource protection and is based on the idea that trust should never be taken for granted and must always be assessed. An all-encompassing strategy for enterprise resource and data security, zero trust architecture covers identity (person and nonperson entities), credentials, operations,...
Chapter
The implementation of the Zero Trust cybersecurity approach has grown more and more important in response to increasingly complex and developing cyberthreats. With Zero Trust, every user, device, and network component is viewed as potentially untrusted, taking a proactive and suspicious approach in contrast to standard security paradigms that rely...
Chapter
In today’s digital landscape, organizations face an ever-growing array of security threats and regulatory challenges. With the proliferation of data breaches, cyberattacks, and stringent regulatory requirements, it has become imperative for businesses to adopt a proactive approach to security and compliance.
Chapter
The goal of the multidisciplinary discipline of cybersecurity is to protect digital networks, systems, and data from harm, unwanted access, and attacks. It entails putting in place a variety of procedures, practices, and technologies to safeguard private data, preserve system integrity, and guarantee data confidentiality, threat recognition, managi...