Dr-Nilamadhab Mishra

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• M.Tech. (CSE), PhD-Eng. (Taiwan), FISRD, FISROSET, SMASR & SMIEDRC (Hong Kong)
• Professor (Associate) at Vellore Institute of Technology University

Integrating AI into the automotive industry has revolutionized driving and interacting with vehicles. This work explores the ethical implications and responsible use of Al in automotive technology. Integrating AI into vehicles represents a major paradigm shift with profound consequences for society, the economy, and individual users. Thus, understa...

This review study examines how the Metaverse has transformed conventional teaching methods into engaging activities that foster student creativity. This study outlines the advantages of the Metaverse within the realm of education. The benefits encompass a tailored educational setting and opportunities for worldwide collaboration. In addition to thi...

Maintaining self-regulating life in old age anticipates high risks and often leads to failure. So, the objective of our study is to inspect the implementation feasibility of an intelligent sensing framework for self-regulating Elderly Health activity supervision. The computational intelligent tools are implemented to frame the intelligent sensing f...

The world of Brain-Computer Interface (BCI) is kind of like a big deal in healthcare. This research paper dives into the many sides of BCI, checking out how it started, works, and integrates with Artificial Intelligence (AI) in healthcare. Starting with a look back in time, the paper follows the path of BCIs from the beginning to now, sharing some...

5G generation has raised significant concerns among the overall public and medical network about its potential influences on human health, especially concerning the implicit risk of cancer and neurological disorders. This debate has mainly become contentious, with a few studies claiming that 5G technology poses dangerous outcomes for human health....

In today's world, the internet and web applications have become extremely popular. In contrast, these applications offer many benefits to organizations, such as fame, profits, etc. They also pose some risks. Malicious attackers take advantage of vulnerabilities in web applications to steal sensitive information. One significant threat is web server...

Machine learning (ML) is the most prominent topic, with many applications in video processing, language processing, visual diagnosis of illnesses, drug development, biochemistry, and biomedical. Healthcare systems and medical science-related applications are rapidly growing among these applications. Large data expansion, the Internet of Things (IoT...

Ethics in computational AI-based approaches have become an inclusive topic of interest among researchers when artificial intelligence has come to light. Doubts have always existed against the ethical implications of introducing artificial intelligence to society. With the advent of artificial intelligence, these voices have only grown louder. Over...

The Internet of Everything (IoE) coupled with Proactive Artificial Intelligence (AI)-Based Learning Agents (PLAs) through a cloud processing system is an idea that connects all computing resources to the Internet, making it possible for these devices to communicate with one another. Technologies featured in the IoE include embedding, networking, an...

Integrating AI-powered adaptive frameworks speaks to a transformative enhancement in instruction, upgrading customized picking up information of things about and optimizing instruction. The paper addresses imperative ethical issues, which envelop records security, algorithmic predisposition, and the need for straightforwardness, highlighting the si...

In this review research study, the authors have discussed how Metaverse has converted traditional, boring teaching methods into fun activities that help teach students creativity. In this study, they explain the benefits of Metaverse in the educational field. Some of the advantages include a personalized learning environment and global collaboratio...

Digitization in the modern world is increasing, and along with it, Cyber-attacks have become a very big concern for individuals, nations, and organizations. In this research paper, we will dive into multiple factors of cyber-attacks and explore their types, perpetrators, impacts, and motivations in depth. We will dissect the different methodologies...

The current study comprehensively investigates Hardware Trojans testing in the cloud using both traditional methods and machine learning models. It highlights the challenge posed by the uniqueness of each Hardware Trojan and emphasizes the need for reliable solutions. The study recommends using machine learning models with feature extraction to det...

As technology advances, so do its diverse and creative inventions. One of those innovations includes smart wearable technology that goes by different names, such as AI-based smart wearable devices or smart wearables. This paper delves into the multifaceted landscape of smart wearable technology, focusing on its integration and susceptibility in les...

The current study comprehensively investigates hardware Trojan testing using traditional and machine learning models. It highlights the challenge posed by the uniqueness of each Hardware Trojan and emphasizes the need for reliable solutions. The study recommends using machine learning models with feature extraction to detect patterns in different H...

Machine learning has become an important tool in healthcare research to solve complex classification problems effectively, efficiently, and quickly. Generally, doctors treat patients according to their medical knowledge and personal experience. Since different professionals have different experiences, they may sometimes make a wrong diagnosis and n...

Sustainable agriculture has significant challenges from sheet and rill erosion for effective techniques. A new way to accurately identify and classifier sheet and rill erosion in agricultural landscapes with the combination of cloud computing and Naïve Bayes. To differentiate between these erosion patterns work proposes a technique that uses ground...

The proposed methodology begins with optimizing deep CNN parameters using Particle Swarm Optimization (PSO) to find an optimal configuration that maximizes the network's performance. PSO aids in the exploration of the high-dimensional parameter space, optimizing CNN's convolutional layers for feature extraction. Subsequently, the CNN is employed to...

Deep learning (DL) is making a significant impact on the lives of human beings, either directly or indirectly; we benefit from Artificial Intelligence (AI), Machine Learning (ML), DL and other technologies/networks in our day-to-day lives. DL not only can mimic a human brain and carry out tasks like a human being but has also outworked the approach...

Animal detection using deep learning leverages advanced machine learning to identify and classify animals in images or videos. This technology has significant implications for wildlife conservation, animal population monitoring, and automated surveillance systems. Deep learning models, especially Convolutional Neural Networks (CNNs), have shown gre...

The proposed work highlights distinguishing characteristics of document content. A significant amount of effort has been put into the field of spam filtering. GANs are an advanced artificial intelligence system that combines the power of two neural networks: a generator and a discriminator. The generator creates data (emails), while the discriminat...

Stock markets are lucrative for individuals and institutions to invest their money. Specific risks are involved when entering any stock market trade; to avoid this, different methods can be adopted, such as fundamental and technical analysis. This paper talks about the machine-learning approach to the stated problem. However, even this method does...

In the competitive area of sports, injuries not only jeopardize athletes' careers but also lead to substantial setbacks for teams and organizations. Addressing this critical issue, our study introduces an artificial intelligence (AI)-driven model that enhances injury management through the strategic implementation of rest periods during athletes' r...

In the contemporary sports landscape, the integration of artificial intelligence (AI) has become pivotal in comprehending and optimizing athletes' performance and well-being. This study focuses on unraveling the intricate dynamics between physical education training, treatment protocols, and the occurrence of sports injuries through an AI-driven an...

In an era defined by data-driven decision-making, businesses grapple with the challenge of retaining their customer base. The work investigates the application of boosting algorithms to predict customer churn, a critical aspect of customer relationship management. In adhering to ethical considerations, the study prioritizes transparency and fairnes...

The authors explore the integration of AI-ML-driven technologies into service marketing, examining their transformative impact on customer engagement, personalization, and operational efficiency. Forex trading is a popular form of investment for investors and entities at many levels. Forex trading or investment is mostly done with the purpose of he...

The effectiveness, efficiency, and security of ICT-monitored systems are assessed as part of the Transnational ICT Leadership Assessment, which is based on the infrastructure currently in place in governmental organizations. Tailoring the assessment to each governmental entity's specific context, organizational structure, and goals is essential. Ad...

In this study, an evaluation of the performance of AI graduates at an Ethiopian university was conducted. This evaluation focused on the extent to which graduates develop their work-ready skills, how well artificial intelligence graduates are performing at the workplace, the skills that hiring organizations expect from artificial intelligence gradu...

Boosting algorithms is one of the greatest tool in machine learning and over the years it has various versions and they all have their own identities. The main objective of the paper is to provide comprehensive study on various algorithms and try to solve a challenging classification problem of customer churn and observe the result of these algorit...

Recent advancements in skin disease identification leverage machine learning for automated diagnosis. However, safeguarding the integrity of sensitive medical data remains a top priority. This paper explores the integration of machine learning and blockchain in skin disease identification preprocessing, promising trust, transparency, and accuracy i...

In a time of escalating digital threats, cybersecurity takes on paramount significance, as website phishing attacks pose considerable risks to individuals and organizations. This extensive survey delves into the ever-evolving realm of website phishing detection, with a specific spotlight on the pivotal role of machine learning-based preprocessing t...

Cryptanalysis is crucial for securing cryptographic systems, particularly with the advent of quantum computing, which threatens traditional encryption methods. Advanced cryptanalytic techniques are essential for developing robust systems that can withstand quantum attacks, ensuring encrypted data remains secure and accessible only to authorized par...

This case-based analysis delves into the intricate web of challenges surrounding the adoption and utilization of information communication technology (ICT) in Ethiopian governmental organizations. By employing a comprehensive framework, the study aims to identify and dissect the prevailing application gap, elucidating the factors contributing to th...

This paper introduces a mobile cloud-based predictive model for assisting Parkinson's disease (PD) patients. PD, a chronic neurodegenerative disorder, impairs motor functions and daily tasks due to the degeneration of dopamine-producing neurons in the brain. The model utilizes smartphones to aid patients in collecting voice samples, which are then...

The development of heterogeneous systems in the environment of smart homes using the Internet of Things (IoT) has been accelerated by recent developments in computer and communication technology. Nevertheless, a large number of these heterogeneous networks are stand-alone and do not adapt to cooperative task execution. As a result, inter-operation...

Recently, there has been a rapid advancement in the usage of smart healthcare systems, especially for the diagnosis of diseases based on imaging technologies, although providing security is challenging. In this scenario, Blockchain is found to be an innate secure method for sharing information based on automated cryptographic techniques for ensurin...

The integration of transnational leadership practices in the field of computing is crucial for Ethiopian universities to enhance their educational quality and keep pace with global advancements. By adopting transnational leadership practices, Ethiopian universities can benefit from international collaborations, knowledge exchange, and access to the...

Medical equipment and applications produce a significant amount of data. This information is moved from one piece of equipment to another and occasionally shared via a global network. So, privacy preservation and security are important concerns in the medical field. Hence, a new medical data-sharing technique is introduced with blockchain for attai...

This research addresses the challenge of automating skin disease diagnosis using dermatoscopic images. The primary issue lies in accurately classifying pigmented skin lesions, which traditionally rely on manual assessment by dermatologists and are prone to subjectivity and time consumption. By integrating a hybrid CNN-DenseNet model, this study aim...

The following specification particularly describes the nature of the invention and how it is performed: FIELD OF THE INVENTION The present invention is in computer science and information technology, specifically addressing dynamic resource allocation in computing environments. More particularly, the invention pertains to utilizing machine learning...

The IoE Grid Computing Framework will be used to look into high-performance computing tools for higher education institutions. The primary and secondary data from higher education organizations are used to make the model and architecture. So, using a computational IoE grid and the supported toolkits, a model of the event was made. To see how well r...

Keeping patient records with diagnostics details is the main aim of digitalized healthcare but health data in traditional storage systems will always attract a risk to data security. There is a high risk of data leak if adequate measurement is not obtained, intruders can modify or delete any of the records. Blockchain is a stable technology that wi...

Speech disfluency, particularly stuttering, can have a significant impact on effective communication. Stuttering is a speech disorder characterized by repetitions, prolongations, and blocks in the flow of speech, which can result in communication difficulties, social isolation, and low self-esteem. Stuttering can also lead to negative reactions fro...

Stuttering, a prevalent neurodevelopmental disorder, profoundly affects fluent speech, causing involuntary interruptions and recurrent sound patterns. This study addresses the critical need for the accurate classification of stuttering types. The researchers introduce “TranStutter”, a pioneering Convolution-free Transformer-based DL model, designed...

It's observed that in recent years, cyber-attacks are becoming a regular threat. In conventional phishing attacks, targeted users are redirected to visit a fake or counterfeit website, for taking out personal information and credentials like banking information, credentials, and even UPI wallets. Usually, phishing attacks happens using email, text...

In order to provide effective techniques for identifying and segmenting organs in high-resolution histology pictures, this research paper introduces a deep learning approach to the HubMAP-Organ Segmentation Competition. The proposed solution combines a Convolutional Neural Network with a U-Net architecture to achieve state-of-the-art performance on...

Mobile cloud computing (MCC), which combines mobile computing and cloud computing, has become one of the industry's most common terms and a major topic of discussion in the IT world. Mobile clients are becoming popular clients for consuming any web resources, particularly web services (WS), as mobile network infrastructures improve. However, there...

The objective of the current investigation is to identify the first or first draining node or sentinel lymph node (SLN) from the primary tumor mass in a regional lymphocenter. Four different indirect lymphography (IL) methods were employed in 96 canine patients with different types of cancer between 2018 and 2021. The IL technique involved intrader...

It is crucial to identify crop diseases early to educate farmers on how to stop the spread of diseases in their crops. However, the agriculture sector's output is impacted by the emergence of numerous crop-related diseases. Multiple methods for predicting paddy leaf diseases have been created, but they still suffer from overfitting, poor detection,...

A visual analysis may accurately predict cardiac arrest, making it a potent educational tool for raising public awareness of health issues. By predicting cardiac arrest earlier, preventative steps can be taken to save lives, and the dissemination of such health knowledge can dramatically lower the world mortality rate. A heart attack, also known as...

Data in medical data warehouses are often used in data analytics and online analytical processing tools. OLAP techniques do not process enterprise data for hidden or unknown intelligence. The data analytics process takes data from a medical data warehouse as input and identifies the hidden patterns; i.e., data analytics process extracts hidden pred...

Artificial intelligence has rapidly grown and has made the scenario that no field can function without it. Like every field, it also plays a vital role in the sports field nowadays. In certain sports, injuries happen very often due to heavy training and sudden speedy actions, especially in athletics and football. Here arises a need to analyze the e...

Logistics is the transfer of goods from one place to another, mostly from the production house to the customers. A logistics network is a set of operations that involve designing, producing, and marketing the goods. Cold-chain logistics are those that needed to be transported in a cold refrigeration right from the production house to the customer....

Green finance can be referred to as financial investments made on sustainable projects and policies that focus on a sustainable economy. The procedures include promoting renewable energy sources, energy efficiency, water sanitation, industrial pollution control, transportation pollution control, reduction of deforestation, and carbon emissions, etc...

Human migration is a challenging process in Ethiopia, where special illegal human migrants cross different border countries without any basic information or knowledge. Due to this, there is the difficulty of getting a vast amount of information to know the destination countries. They go without any information, which also wastes more time, cost, vi...

The forecast for software vulnerabilities seeks to decrease test automation expenditures by leading users to default enterprise software categorization. In so many businesses, defect predictors are frequently used to prevent software defects to save time, improve quality, testing, and improve resource allocation to meet schedules. The implementatio...

Internet of Things (IoT) is distressing this global with its creating implementations in various pieces of growth, for instance, medicinal services, detecting, and far off checking, and so on. Cell phones and apps are executing effectively to recognize the vision of the IoT. Starting later, there is a quick increase in dangers that are added, virus...