Dr. Saikat Gochhait

Symbiosis Institute of Digital and Telecom Management, Symbiosis International Deemed University

What do sex and spirituality have in common? They are currently the top two marketing models for promoting products as varied as chocolate, athletic clothes and cars. Perhaps it’s due to the extensive use of sex in advertising, but recently, spirituality has gained momentum and become advertiser’s number one tool to attract and sell. This emerging...

In the era of digital communication, it is more about being able to detect emotions than anything else if we are to maintain this complicated and demanding human society. Emotion recognition research is pulling out all the stops, resulting in all manner of methods to recognize human feelings. Emotions are often transmitted through words and body la...

Human Activity Recognition for Fight Detection is an important research domain aimed at automatically identifying patterns indicative of physical altercations. Lever-aging deep learning models like CNNs and RNNs, this approach extracts features from video frames to recognize fight-related behavioural patterns. The primary objective is to develop a...

Increase in population and trend for luxurious lifestyle has led to huge increase in the number of vehicles. This change has further fascinated the researchers to focus on smart transportation systems. Numerous applications are offered in smart transportation systems like smart parking, detecting event of accidents, smart lights, and many more. Det...

This study focuses on impulsive Volterra-Fredholm integro-differential equations (VFIDEs) under specific order conditions, conducting a rigorous analysis involving fractional Caputo derivatives. By applying the Schauder fixed-point theorem, we prove the existence of solutions and examine the interaction between fractional Caputo derivatives and the...

Accurate long-term load forecasting (LTLF) is crucial for smart grid operations, but existing CNN-based methods face challenges in extracting essential features from electricity load data, resulting in diminished forecasting performance. To overcome this limitation, we propose a novel ensemble model that integrates a feature extraction module, dens...

URL stands for uniform resource locator are the addresses of the unique resources on the internet. We all need URLs to access any type of resource on the internet, such as any web page, and document. Sometimes URLs can be long, irrelative and unattractive and unable to send sometimes via email. So, for this, we proposed a URL shortener web applicat...

This paper introduces a novel nature-inspired optimization algorithm called the Addax Optimization Algorithm (AOA), which emulates the natural behavior of addax in the wild. The core inspiration for AOA is drawn from the addax's foraging strategy and digging skills. The theoretical foundation of AOA is expounded and mathematically modeled in two ph...

In this article, a new human-based metaheuristic algorithm named Dollmaker Optimization Algorithm (DOA) is introduced, which imitates the strategy and skill of the dollmaker when making dolls. The basic inspiration of DOA is derived from two natural behaviors in the doll making process (i) making general changes to the doll-making materials and (ii...

In this chapter, the authors aim to discuss the significance of integrating AI prediction and green computing in the healthcare field to improve disease diagnosis, treatment, and patient care and minimise the adverse effects on the environment. The methodology employed is the systematic literature review (SLR) approach. The results show that combin...

AI is rapidly transforming the field of epidemiology. This chapter explores how AI integrates data analysis, predictive modeling, disease surveillance, and diagnostic tools to significantly improve public health outcomes. AI-driven methodologies enhance diagnostic accuracy, improve disease surveillance efficiency, and aid in developing better predi...

The burgeoning field of AI-powered healthcare prognosis offers immense potential, but traditional data center infrastructure creates a significant environmental footprint. This chapter advocates for energy-efficient AI algorithms and hardware alongside renewable energy integration (solar, wind) to minimize reliance on fossil fuels. Robust security...

Clinical trial design is undergoing a revolution fueled by artificial intelligence (AI) and translational bioinformatics. This chapter explores how AI techniques like machine learning and deep learning are being harnessed to analyze vast datasets of biological and clinical information. By integrating these insights with translational bioinformatics...

Accurate disease prognosis is crucial for improved healthcare outcomes. Artificial intelligence (AI) offers immense potential in this domain, but traditional “black-box” models lack interpretability. This chapter explores the integration of Explainable AI (XAI) with Green AI, a resource-efficient and sustainable approach to AI development. They dis...

This chapter explores the potential of green AI and big data informatics for personalized disease prediction in clinical decision making. Green AI prioritizes efficiency, minimizing computational resources needed to analyze vast healthcare datasets. Big data informatics provides the platform to manage and analyze these datasets for knowledge discov...

Cloud computing is gaining momentum as a subscription-oriented paradigm providing on-demand payable access to virtualized IT services and products across the net. It is a breakthrough technology that is offering on-demand access to various services across the network. Auto-scaling, though quite an attractive proposition to customers and naïve cloud...

CDN is constituted of three basic components. A content provider is somebody entrusting the URI namespace of the Web objects to be dispersed. The content provider's server contains all such objects. A CDN provider can be some owner party that enables transportation conveniences to content providers to deliver content in a timely and reliable manner...

This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization (FLO), which emulates the unique hunting behavior of frilled lizards in their natural habitat. FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards. The algorithm’s core principles are meticulously detailed and math...

Physician-written discharge medical notes include vital details regarding their patients' health. Numerous deep learning algorithms have shown effective in gleaning crucial insights from unstructured medical notes data, leading to potentially useful outcomes in the medical field. The goal of this research is to determine how different deep learning...

Impact statement In Sub-Saharan Africa, the burgeoning field of internet banking promises to revolutionize financial services, offering unprecedented convenience and accessibility. However, despite its potential, the widespread adoption of Internet banking services in the region face significant hurdles. This research endeavors to illuminate and di...

Mustard plants are a crucial agricultural commodity for food and oil production. However, they are frequently vulnerable to various diseases that can substantially reduce crop yield. Early identification and diagnosis of these illnesses are essential for efficient management and control, ensuring sustainable production and agricultural output conti...

Skin cancer is one the most frequent type of cancer in the world. Early detection and diagnosis are vital for effective treatment. Deep learning has been determined to be efficacious in the categorization of skin cancer. In this paper the author has presented a deep learning approach for classifying skin cancer. The algorithm was trained on approxi...

The global COVID-19 pandemic has resulted in significant loss of life and profoundly affected every aspect of human existence. A noteworthy area of study in this crisis is the use of deep learning (DL) models in medical imaging for the treatment of patients with COVID-19. This in-depth research delves into various methods of medical imaging, such a...

This paper aims to investigate how artificial intelligence (AI) can improve cybersecurity and internal audit practices. In today's world, organizations are facing an increasing number of sophisticated cyber attacks and are actively searching for new methods to safeguard their sensitive information and systems. AI has emerged as a promising solution...

In recent years, heart disease has become a very serious threat to the health and safety of people all over the globe. Typically, this condition occurs when there is an insufficient supply of blood from the heart to various parts of the body, which hampers their usual operations. Early and timely detection of this disease holds paramount impo...

A new bio-inspired metaheuristic algorithm named the Pufferfish Optimization Algorithm (POA), that imitates the natural behavior of pufferfish in nature, is introduced in this paper. The fundamental inspiration of POA is adapted from the defense mechanism of pufferfish against predators. In this defense mechanism, by filling its elastic stomach wit...

Effective energy management is crucial for sustainability, carbon reduction, resource conservation, and cost savings. However, conventional energy forecasting methods often lack accuracy, suggesting the need for advanced approaches. Artificial intelligence (AI) has emerged as a powerful tool for energy forecasting, but its lack of transparency and...

After a growing concern for the environment, those involved in the environmental movement began to produce ecologically friendly products. Therefore, the article explores the possibility of creating a hybrid digital currency PCoin through eco-design. This approach is used to implement a more efficient and environmentally friendly way of handling tr...

The field of higher education in India is plagued by various fraudulent institutions and actors who profit at the expense of students and parents, for example, by issuing fake course completion certificates, which adversely affect the quality of teacher education. This paper presents a possible solution in the form of a model in which a digital rec...

In this paper, a new bio-inspired metaheuristic algorithm called Giant Armadillo Optimization (GAO) is introduced, which imitates the natural behavior of giant armadillo in the wild. The fundamental inspiration in the design of GAO is derived from the hunting strategy of giant armadillos in moving towards prey positions and digging termite mounds....

Background: In the last decade, the concept of the Glymphatic system as a complexly organized perivascular transport has been formed, it “connects” the cerebrospinal fluid with the lymphatic vessels of the meninges through the extracellular space of the brain. The exact molecular mechanisms of the functioning of the glymphatic pathway have not been...

Aims Load forecasting with for efficient power system management Background Short-term energy load forecasting (STELF) is a valuable tool for utility companies and energy providers because it allows them to predict and plan for changes in energy. Method: 1D CNN BI-LSTM model incorporating convolutional layers. Method 1D CNN BI-LSTM model incorpo...

Street lighting is an important concept on which we have to focus more because we spend more than 40 percent of the allotted budget towards it. In the present scenario most of the street lighting systems are inefficient in reducing the cost. An effective solution is reducing the energy consumption. This paper deals with monitoring and controll...

We wanted to find out how English-foreign language learners (EFoLLe) utilize OILL apps, a prominent social networking site for language learning, and how they feel about it as a MALL tool. Roxetta Stone, Duolingo, and Daily Learn English were also studied to see whether any specific EFoLLe profiles emerged when it came to using them for self-paced...

The objective of the research is analyzed and help provide a prediction model for similar diseases by using MERS and SARS data. There are examples of companies like BlueDot which used AI analysis of data points from multiple resources and predicted the outbreak in December 2019 mid. Using big data will have its advantages because we can use data fr...

Human beings do not have enough time to consult a doctor on a regular basis about their health because of their heavy workload and lack of time. It becomes difficult for the patients to visit multiple hospitals multiple times for their examination. With Healthcare 4.0 and fog computing a large quantity of information can be processed which can gene...

Breast cancer is the second leading cause of mortality among women. Early and accurate detection plays a crucial role in lowering its mortality rate. Timely detection and classification of breast cancer enable the most effective treatment. Convolutional neural networks (CNNs) have significantly improved the accuracy of tumor detection and classific...

Currently, women are widely recognized as successful entrepreneurs because of their strong desire, qualities, and abilities in order to drive robust economic development in their respective countries. In light of women's significant contribution to economic development in India, the study investigated factors that affect women entrepreneurs' succes...

In the wake of grid modernization initiatives, such as the integration of renewable energy sources and demand response, as well as the increasing popularity of electric vehicles, a greater degree of uncertainty has been introduced due to the fact that electricity demand has become more active and less predictable, and forecasting load has become in...

https://ieeexplore.ieee.org/author/37088479695

Purpose: This experimental study was conducted during the post-COVID-19 period to investigate the relationship between the quality of life 9 months after and the severity of the SARS-CoV-2 infection in two scenarios: hospitalization (with/without medical oxygen) and outpatient treatment. Methods: We employed the EQ-5D-5L Quality of Life tests an...

Digital twin technology is the union of three systems - the physical, the virtual and the interconnecting link layer. It acts as a replica and provides real-time representation of real-world physical objects in a virtual format. Digital twins are promising when applied in healthcare. This brief review gives a schematic overview of the current state...

Healthcare cybersecurity has surfaced as the industry’s greatest serious extortions. The potential dangers of Web-based healthcare systems have rapidly increased, attracting the hacker community. When patient health records are digitized, there is a risk that sensitive health information will be compromised, and sensitive data may be leaked to hack...

During the COVID-19 pandemic, the world has witnessed rampant use of digital technology in almost every facet of huma lives. However, these digital techniques like use of mobile apps have certain drawbacks and constrains. These could be addressed with the use of emerging technologies like Internet of Things (IoT). In healthcare, that is Internet of...

https://www.mdpi.com/journal/entropy/special_issues/ICBNA_2022

The field of biology has evolved into a data research discipline and an enormous amount of data has been sequenced and is available for synthesis. There is therefore a need for careful storage, organization, synthesis and analysis of large data sets in order to discover relevant knowledge. Thus, information technology and computation techniques are...