Browse Items (1422 total)
Sort by:
-
Assessing Climate Change through Artificial Intelligence An Ethico-Legal Study
IPCC (The Intergovernmental Panel on climate change) [1], in the 6th Assessment Report released in 2022, reports that the net anthropogenic GHGs (greenhouse gases) continued to rise during the period 2010-19. It shows that GHG emission in the last decade is the highest in human history. According to the World Inequality Report, 2022, carbon dioxide concentration level in the atmosphere across the globe is the highest in millions of years. Consistent rise in the global emission level leading to alarming rise in atmospheric temperature has been a cause of concern for mankind. Rising atmospheric temperature leading to climate change has severely affected weather patterns; led to melting of glaciers; caused natural disaster and extinction of species, and severely impacted the ground water table. It has put the human race at a crossroads and thrown open an existential question for the world. Attempts have been made, both international and national, to reverse the impact of the rising scenario concerning climate change but have yet to be successful. The technological revolutions arising in recent times, especially in the domain of Artificial Intelligence (AI), offer hope to give a new shape to human civilization. With the aid of human intelligence, AI can perform assessment and predictive work as well which may help in mitigating the effect of adversely affecting climate change and help improve the environment. As per UNESCO (United Nations Educational, Scientific and Cultural Organisation), AI can perform assessment and prediction of climate change, which may assist in the protection of the environment. The Council identifies three priority areas relating to use of AI which includes improved understanding and predictions of climate change and geohazards [2]. This chapter aims at exploring the contribution of AI in assessing the behavioral pattern of climate change and the ethico-legal challenges involved therein. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
Symbiotic cyanobacteria in gymnosperms
Cyanobacteria are a widespread group of phototrophic bacteria that are morphologically diverse and present on almost every environment on earth. Many cyanobacteria are able to fix atmospheric nitrogen and thus are able to form symbiotic association with a wide range of eukaryotic hosts such as plants, fungi, sponges, and protists. Cyanobacteria are able to provide carbon to nonphotosynthetic hosts such as fungi, but their primary role is to supply fixed nitrogen to enable the host to flourish in nitrogen poor environments. In turn, cyanobionts get the benefits of protection from competition, predation, and environmental extremes. Of all the cyanobacterial symbiotic associations, this chapter focuses on understanding the symbiotic association between gymnosperm and cyanobacteria. Species belonging to phylum cycadophyta are associated with nitrogen-fixing cyanobacteria (Nostoc species) through small specialized roots called coralloid roots. The cyanobionts are expected to have a heterotrophic mode of carbon nutrition, due to their location in coralloid roots (complete darkness). 2023 Elsevier Inc. All rights reserved. -
Blockchain Using Wireless Technology
In today's dynamic digital landscape, blockchain technology emerges as a pioneering force with the potential to redefine industries and transform the way we conduct business, share information, and establish trust. This chapter explores the foundational concepts of blockchain technology, its versatile applications, and the profound impacts it can have on various sectors. While blockchain holds immense promise, challenges like scalability, energy consumption, and regulatory frameworks must be addressed. Decentralized apps and smart contracts introduce new vulnerabilities that demand vigilant management. The integration of blockchain with wireless technology expands opportunities and streamlines processes. Wireless connectivity enhances accessibility, reach, and interaction with blockchain applications, benefiting finance, supply chain, and healthcare sectors. Real-time data sharing and reduced infrastructure reliance boost productivity. Environmental concerns, including blockchain's energy consumption and e-waste from wireless devices, need mitigation. In conclusion, the fusion of blockchain and wireless technology offers tremendous potential but demands a delicate balance between technological progress and environmental stewardship. Addressing reliability, security, scalability, and environmental impacts through innovative solutions and ethical practices is vital for a connected and sustainable future. 2024 CRC Press. -
Adoption of Sustainable Digital Technologies in Industry 4.0
We are living in a society that has been engulfed with growing technology, and the integration of it has become such an important part of our lives that it is scary to think of our daily lives without mobile phones, internet, or smart gadgets. Industry 4.0, briefly, means using new age technologies such as cloud computing, artificial intelligence, machine learning, Internet of Things, and big data in the different real-world applications of manufacturing, processing, and distribution of goods and services. Industry 4.0 involves making use of smart factories and technologies to minimize waste and to gain an absolute advantage in the development process. We already know the different use cases of these technologies and how these things help in lessening our workload, so it seems logical to apply them to broader aspects of our daily lives. Technologies mitigate our workload and improve efficiency. We have seen that these technologies are proving useful in different spheres of economics, with the help of new decision-making processes, model predictions, and even to improve healthcare. Through the scope of this chapter, we would shed light on how these different technologies are being incorporated and how these would help in stabilizing industry by its constant integration. 2024 selection and editorial matter, Vandana Sharma, Balamurugan Balusamy, Munish Sabharwal, and Mariya Ouaissa. -
Sustainability disclosure and green finance: Driving the transition towards a sustainable future
In recent times, policymakers and scholars have directed their attention toward the notion of sustainability and green finance, coinciding with the growing global emphasis on environmental protection, climate change mitigation, and sustainable development. The integration of sustainability and green finance practices has emerged as a crucial strategy to address climate change, advance sustainable development goals issues, and build a resilient global economy in the face of pressing environmental challenges. The adoption of green finance and sustainability practices is no longer limited to developed economies. Many developing and under-developed countries are also taking a proactive approach to develop and implement a roadmap and framework for incorporating sustainability. In this chapter, the authors explore the notion of green finance, its crucial role in advancing sustainability, and the substantial consequences it can bring about for diverse businesses and stakeholders. 2023, IGI Global. All rights reserved. -
E-Commerce data analytics using web scraping
Some companies, like Twitter and others, provide an application programming interface (API) to fetch the information. If the API is not available, we will have to search other websites to get the data in a structured format. The primary way to get data from a web page is through web scraping. The basic idea of web scraping is to pull data from a website and convert it into a format that can be used for analysis. In this paper, we will discuss the simple explanation of how we can use Beautiful Soup to scratch data into Python and later save the extracted data in an Excel spreadsheet and do the spreadsheet analysis later. We will pull data from the Flipkart website to know the cell phone name, cell phone price, cell phone rating, and cell phone specification. 2023 Scrivener Publishing LLC. -
Predictive analysis of stock prices through scikit-learn: Machine learning in python
Scikit-learn, a tool for developing machine learning algorithms, is a standard library of python. Through Scikit-learn, a trained model for predictive analysis can be developed. Such models aim to provide accurate predictions. Stock predictions are based on changes and patterns identified in the historical dataset. Following the trends and patterns of the historical changes of stocks, machine learning algorithms can be developed for achieving accurate outcomes. An effective model is developed, which enhance the working pattern or performance of the machine that further helps to draw a precise analysis of stocks. 2023 Scrivener Publishing LLC. -
Implementation of tokenization in natural language processing using NLTK module of python
With the advancement of technologies, now it is possible to analyze the large amount of unstructured text circulated online with various tools and methods for understanding the changes as well to infer meaningful insights from the text data. In this work, the aim is to understand how Python can be used for text analytics by the help of various libraries available in it. The natural language processing (NLP) is being used to analyze and synthesize natural language and speech in Python. 2023 Scrivener Publishing LLC. -
Performance analysis and interpretation using data visualization
The matrix plot library (Matplotlib) is a unique feature in python that helps in the visualization of data via entering certain dataset and codes. It is a portable two-dimension of plot and images are mainly focused on visualizing scientific, technical, and financial data. These matrix plots are performing with the help of python programming and various user interface applications. Most familiar versions of joint photographic and supportable picture graphics are used for the picture visualization. These additional features include the various navigation processes, pages with the line, as well as images. The financial charts of open source website are used for tables and mathematical texts. The library is based on numerical python arrays, giving us visual access to massive quantities of data in readily consumable graphics. The problem statement here delves further into the functions of this feature, which will aid in a better understanding of Python's involvement in the data visualization. 2023 Scrivener Publishing LLC. -
Dealing with missing values in a relation dataset using the DROPNA function in python
Python provides a rich data structure library called PANDAS, which provides fast and efficient data transformation and analysis. The word PANDAS is an abbreviation of Python Data Analysis Library. PANDAS facilitate optimized and dynamic data structure designs work with "relational" or "labeled" data. Python's approach is meant to provide a high-level, high-performance building block that can be used to do real-world analysis of data. PANDAS Library is allowing users to import data from different file formats, such as CSV, SQL, Microsoft Excel etc. [1]. It helps in data preparation, as well as in data modeling, for those projects, which aims data analysis for the extraction of information. Python's future will be built on this layer for statistical computing. In addition to discussing future areas of work and growth opportunities for statistics and data analytics applications built on Python, the study provides details about the language's design and features [2]. In this research paper, we intend to solve the problem of missing values in a dataset using the DROPNA function in Python using PANDAS library. 2023 Scrivener Publishing LLC. -
A Qualitative Enquiry of the Experience of Music Professionals during the COVID-19 Pandemic
Introduction: The COVID-19 pandemic became a new normal in todays world and has changed the consumption pattern and absorption of music and music apps in India. The music industry is relatively non-telecommutable, making working from home difficult during the imposed lockdown and social distancing norms. These conditions had adverse effects on the physical and mental health of music professionals. Therefore, it was crucial to understand the differential impact of COVID-19 on music professionals to find effective solutions and plan for future careers in a changed music industry. Method: The current paper qualitatively explored the experiences of the music professionals participating in this research during the COVID-19 pandemic in India. Twelve participants having 8 years of average professional experience (comprising singers, instrumentalists, music teachers, composers, YouTube content creators) were telephonically interviewed during the second wave of COVID-19 in India. The interviews were analysed using thematic content analysis. Results: The thematic content analysis resulted in the emergence of two major themes identified from the participants narratives were impact on participating music professionals and coping reactions. Conclusion: The themes emerged from analysis highlighted the impact of COVID-19 on these music professionals and the coping reactions utilized by them. 2025 selection and editorial matter, Dr Uzaina, Dr Rajesh Verma with Dr Ruchi Pandey; individual chapters, the contributors. -
Effective Temperature Prediction for An Enhanced Climate Forecast System
Ever since the first industrial revolution, there has been a subtle temperature change. The transition to new manufacturing processes in conjunction with the surge in population has a negative consequence on the earths atmosphere. Climate change has been identified as the most crucial environmental issue of this century, and it has sparked heated discussions [1]. Temperature is the most common metric to evaluate the change in climate/global warming. It is anticipated that climate change will result in an adverse and enduring impact on the ecosystem. Weather forecasting today extensively depends on conventional methodologies and requires complex and complicated infrastructure [2]. Prime problems concern quality of acquired data, timeliness, availability, reliability, and usability constraints on forecast preparation. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
A review of reinforcement learning approaches for autonomous systems in industry 4.0
[No abstract available] -
Pathway toDetect Cancer Tumor byGenetic Mutation
Cancer detection is one of the challenging tasks due to the unavailability of proper medical facilities. The survival of cancer patients depends upon early detection and medication. The main cause of the disease is due to several genetic mutations which form cancer tumors. Identification of genetic mutation is a time-consuming task. This creates a lot of difficulties for the molecular pathologist. A molecular pathologist selects a list of gene variations to analyze manually. The clinical evidence strips belong to nine classes, but the classification principle is still unknown. This implementation proposes a multi-class classifier to classify genetic mutations based on clinical evidence. Natural language processing analyzes the clinical text of evidence of gene mutations. Machine learning algorithms like K-nearest neighbor, linear support vector machine, and stacking models are applied to the collected text dataset, which contains information about the genetic mutations and other clinical pieces of evidence that pathology uses to classify the gene mutations. In this implementation, nine genetic variations have been taken, considered a multi-class classification problem. Here, each data point is classified among the nine classes of gene mutation. The performance of the machine learning models is analyzed on the gene, variance, and text features. The gene, variance, and text features are analyzed individually with univariate analysis. Then K-nearest neighbor, linear support vector machine, and stacking model are applied to the combined features of a gene, variance, and text. In the experiment, support vector machine gives better results as compared to other models because this model provides fewer misclassification points. Based on the variants of gene mutation, the risk of cancer can be detected, and medications can be given. This chapter will motivate the readers, researchers, and scholars of this field for future investigations. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Mobile apps in bleisure tourism: Enhancing travel experience, work-life balance, and destination exploration
This study aims to achieve four primary objectives: first, to evaluate how mobile apps improve travel productivity and efficiency by streamlining logistics and simplifying planning for both business and leisure activities; second, to investigate how these apps support the integration of work and leisure by providing tools for remote work, task management, and peer communication; third, to explore how mobile apps enhance the quality and authenticity of bleisure experiences by helping travelers discover new places and immerse themselves in local culture; and finally, to construct a comprehensive framework for mobile apps in bleisure tourism for use by multiple stakeholders, including travelers, travel companies, the hospitality industry, employers, local tourism boards, and app developers. This study highlights the significance of mobile technology in optimizing the bleisure travel experience. 2024 by IGI Global. All rights reserved. -
Sacred gastronomy trails: Exploring the divine fusion of religion, food, and tourism
This study seeks to explain the complex relationships among these three constantly evolving fields, i.e., religion, food, and tourism. The primary objective is to examine the strong link between food and religion by breaking down culinary customs and examining how they influence the formation of gastronomic identities across a range of religious traditions. The second objective explores the connection between food and travel, with a special emphasis on the cultural relevance of pilgrimage food travels. The third goal is to broaden the investigation to include the connection between religion and travel. Through the integration of results from the three aforementioned goals, the research aims to develop a theoretical framework that elucidates the intricate relationship between these components, offering a thorough comprehension of the interdependence of religion, cuisine, and travel in forming personal encounters and cultural environments. 2024 by IGI Global. All rights reserved.. -
Mobile Apps for Enhanced Bleisure Tourism Experiences: Exploring the Prospects and Challenges
Mobile applications play a pivotal role in enabling and enhancing bleisure travel experiences. These apps offer solutions for communication, itinerary planning, transportation booking, and leisure discovery, reflecting the evolving expectations of modern travelers for efficiency, flexibility, and customized experiences. Despite their benefits, challenges such as data privacy concerns and information overload persist. Looking ahead, the future of bleisure travel is poised for further transformation through advances in mobile technology, including augmented reality and artificial intelligence. However, a research gap exists in understanding the full spectrum of mobile apps catering to bleisure tourists' needs. This chapter aims to address this gap by classifying mobile apps for bleisure tourism, exploring their advantages, and identifying challenges and opportunities for innovation. By doing so, it seeks to contribute to a deeper understanding of the role of mobile technology in shaping the landscape of bleisure tourism in the digital age. 2024 by IGI Global. All rights reserved. -
Disrupted Diners: Impacts of COVID-19 on Restaurant Service Systems and Technological Adaptations
Measures such as lockdowns and social distancing may have effectively controlled the pandemic, but they have a tremendous detrimental effect on businesses relying heavily on face-to-face communications such as the restaurant and dine-in industry. With the current COVID-19 pandemic, the restaurant and dine-in places had to face the brunt of losing customers due to government-mandated public health measures. The restaurant sector had to look for an overhaul immediately as the disruptions caused by the pandemic has pushed them either on the verge of closure or bad financial health. Nevertheless, an upsurge of technological advancements has come as a lender of last resort to the restaurant industry. This chapter presents the major disruptions caused by the pandemic in the in-person dining sector. It also sheds light on the various methods shaping the future of the restaurant industry. Finally, the chapter deals with the different prospects and challenges awaiting the paths of transformation and draws a framework called The Dining Spectrum as a contribution to the existing literature. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
COVID-19, religious events, and indian tourism recovery: Prospects and paradoxes
The chapter delves into three objectives. Firstly, the chapter aims to find out the intersectionalities of religious events and the Indian tourism industry. For the second objective, the impact of the COVID-19 disease on religious events will be briefly discussed. Lastly, this work will discuss the various emergent prospects, themes, trends, and challenges that will emerge on the paths of the recovery of religious events and pilgrimage tourism post-COVID-19. This work is theoretical in nature and can be classified as a viewpoint article that follows a conceptual research design. Copyright 2023, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. 2023 by IGI Global. All rights reserved. -
Introduction
[No abstract available]