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Business Forecasting and Error Handling Using AI
Business forecasting is the technique of accurately predicting the future of a business and outcomes using historical data and present trends. To evaluate historical data and find patterns, trends, and other elements that might be used to forecast future events, a variety of analytical tools and techniques are used. Business forecasting is a crucial component of strategic planning because it enables businesses to foresee market changes, spot possible risks and opportunities that may arise in the future, and make wise resource allocation and investment decisions. Businesses that use effective business forecasting can plan and carry out their programs that help them stay competitive, expand their operations, and meet their objectives. According to Glueck [1], Forecasting is a formal process of predicting future events that will significantly affect the functioning of an enterprise.. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
In vitro production of bacosides from Bacopa monnieri
Bacopa monnieri (L.) Wettst. (Plantaginaceae) is an important Ayurvedic medicinal herb commonly known as brahmi, growing in the region of Indian subcontinent. Bacosides are the major chemical component having the major role in the biological and pharmacological field. Bacopa cultivation is time-consuming, requires labor team, and needs great efforts to maintain the quality of bacosides as growths are affected by environmental factors such as soil, water, temperature, climate, pests, and pathogens. To solve these problems, organ and cell cultures have been adopted for swift and efficient production of Bacopa biomass and bacosides. In the current chapter, various parameters, such as types of media, media composition, elicitors, salinity, drought, types of vessels used, and effect of heavy metals, were investigated against the in vitro production of bacosides from Bacopa monnieri. Springer Nature Singapore Pte Ltd. 2018. -
In vitro propagation and secondary metabolite production from Withania Somnifera (L.) dunal
Withania somnifera (L.) Dunal, commonly known as ashwagandha or Indian ginseng, is an important medicinal plant that belongs to the family Solanaceae. Ashwagandha has been used from time immemorial in different systems of medicine and extensively used in the Indian system of medicine, and there is discussion of this plant in different ayurvedic scripts like Charaka samhita, Ashtanga sangraha, etc. The plant is extensively used for anti-aging and general well-being, and also has anti-cancer potential. Ashwagandha is also known for its antioxidant, anti-inflammatory, and other therapeutic activities. In the recent days of Covid-19, the plant has been extensively used as an immunostimulant. The plant has great potential for its raw materials, especially for the extraction of bioactive molecules like withanolide-A, withaferin-A, withasomniferin, withanone, etc. The conventional mode of propagation could not meet the required commercial demand for either the pharmaceutical industries or the traditional practitioners. The conventional method of obtaining biomass is influenced by a large number of environmental factors, where biomass quality and quantity of bioactive molecules have shown variation. To overcome this, biotechnological approaches such as plant tissue culture techniques have been established for large-scale cultivation using micropropagation and also other techniques like a callus and cell suspension culture, shoot culture, adventitious root culture, and hairy root culture have been extensively used for in vitro production of bioactive molecules from ashwagandha. With the advent of metabolic engineering, biosynthetic pathway editing has made it possible to obtain higher yields of desired metabolites. The present chapter focuses on the in vitro propagation, biosynthesis of withanolides, and tissue culture strategies for obtaining high biomass and metabolites. The chapter also focuses on different elicitation strategies, metabolic engineering approaches, and the development of elite germplasms for improved metabolite content. The chapter also identifies research lacunas that need to be addressed for the sustainable production of important bioactive molecules from ashwagandha. 2024 Bentham Science Publishers. All rights reserved. -
In Vitro Production of Saponins
Plants have been utilized as food, feed, and fodder since the dawn of civilization. Plants are also thought to be a rich source of bioactive compounds with a variety of pharmacological actions. Saponins are one such group of molecules which are present in various plant species. As triterpenoid glycosides, they have a 30C oxidosqualene precursor aglycone moiety (sapogenin), which is then linked with glycosyl residues to form saponin. These saponins have a unique platform in the field of pharmaceutical and nutraceutical industries. Saponins are used for the treatment of various diseases which include cancer, diabetic, cardiac, hepatic, and nervous disorders. The production of saponins through conventional approaches is time-consuming and hard to extract pure compounds, and thus to achieve this, in vitro methods have been developed and enhanced the production and extraction of the metabolites. The present chapter focuses on the in vitro production of saponins through various tissue culture techniques such as shoot, callus, cell suspension, adventitious root, hairy root culture, and applications of bioreactors at commercial level. The chapter also focuses on biosynthetic pathway, extraction methods, and biological activities of saponins. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
A Citation Recommendation System Using Deep Reinforcement Learning
Recommender systems have seen tremendous growth in the last few years due to the emergence of web services like YouTube, Netflix, and Amazon, etc. An excessive amount of data is being utilized to give proper recommendations to the users. The number of research articles getting published every day is increasing exponentially and thus an efficient model is required to provide accurate and relevant recommendations to the research scholars. The proposed Deep Reinforcement Recommender for Citations (DRRC) model uses reinforcement learning to train the available citation network to achieve the most relevant recommendations. The proposed DRRC model outperforms the state-of-the-art models. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Carbon-Based and TMDs-Based Materials as Catalyst Support for Fuel Cells
Global energy consumption and environmental pollution caused by the extensive use of fossil fuels have increased the need to look forward to more renewable energy sources. Fuel cell, one of the promising energy conversion devices, has the potential to outsmart the existing devices but has several setbacks to be employed on a larger scale. One of the hindrances is the sluggish oxygen reduction reaction kinetics at the cathode and hence requires electrocatalysts to improve its overall performance. This chapter provides a brief overview of graphene and transition metal dichalcogenides (TMDs)- based composites that have the potential to be used as a catalyst support. 2024 World Scientific Publishing Company. -
ARise to the occasion: Elevating customer engagement
Augmented reality (AR) is being used to transform the landscape of online retail by enhancing customer engagement and experience. This chapter delves into how AR's unique capabilities, such as virtual try-on and interactive product visualisation, can overcome the limitations of traditional online shopping and create deeper connections between brands and consumers. It explains how AR personalises the customer journey by providing customised product recommendations and immersive virtual experiences that drive purchase decisions. By analysing past implementations and future trends, this chapter demonstrates how ARM can usher in a new era of customer engagement and personalised experiences in online retail. 2024, IGI Global. All rights reserved. -
"Case" as "text" in the class: Plethora of pedagogical and structural nuances
The research work undertakes to examine "case, ? "case study, ? and "case pedagogy. ? As the first step, the chapter explores the feel of the Case. This leads to a further investigation and lets out certain malfunctions: gross lapses, loopholes, casualties, and shortcomings. Case then has been subjected to further investigations. Keeping intact the primary concerns of case scan and its explications thereupon, the study takes up the interpretations and intricacies involved in understanding the case. These expose the puzzles involved in the pedagogical exercises in educational institutions. The research with astute expedience does the operation with logical reasoning. The work leads to proper remedial measures and redefines case and case grasp. Using theory of ontology, case is subjected to closer examination. Theory of epistemology further deepens research pursuits to unravel a few more case mysteries. From these, the authors evolve a few keys and tips to study case more effectively. All help readers build up exemplary teaching methods and effective learning concepts. 2022, IGI Global. All rights reserved. -
Advanced Materials from Biomass and Its Role in Carbon-Di-Oxide Capture
This chapter explores utilizing agricultural waste for developing advanced materials for CO2 capture, overcoming drawbacks of conventional adsorbents. It compares biomass-based activated carbons CO2 adsorption capabilities to commercial adsorbents, highlighting promising performance. Strategies for enhancing selectivity and efficiency through functional group hybridization are discussed, alongside investigations into operational parameters effects on material properties and CO2 uptake. Additionally, the chapter reviews biomass-derived carbon materials role in CO2 capture, detailing conversion techniques like pyrolysis and hydrothermal carbonization. Various modification methods, including activation and N-doping, are examined for enhancing CO2 capture. Discussion extends to diverse advanced materials derived from biomass, including biochar and activated carbon. The chapter underscores the circular-economy impact of utilizing biomass-derived porous carbons in CO2 capture processes, particularly in biogas upgrading to biomethane. Overall, it offers insights into addressing CO2 capture challenges, proposing future research directions in this field. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
"The sense" and its manifestations launch new trends in marketing
The chapter investigates the latest developments in marketing and consumer science. The study deepens and strengthens the prospects of marketing. In the process, human sense plays a vital role. The study seeks the assistance of hermeneutics to understand the permutations and combinations generated by a plethora of multifarious conceptual variations in both perception and aesthetics. The "sense" influences marketing of goods and products in business. The proposed configurations relate business functions with aesthetic characteristics. The first part by the research picks the application of senses in the perception level. The second part the researcher chooses sense in the cognition level. The whole study substantiates how Aesthetics and Sense during last decades generate a fast progress in business and marketing. 2024, IGI Global. All rights reserved. -
Mind and Nature: Study on Mental Health, Nature Connectedness, Pro-Nature Conservation Behaviors and Geographical Green Cover among Indian Adults
For centuries the relation between mind and nature has been represented through literature, songs and cultural traditions. However with increasing urgency of the climate crisis and the corresponding growing distance between humans and nature, we find very limited scientific work exploring their relationship, which could perhaps help re-bridge the connection between the two. A significant, yet not directly observable, and often overlooked impact of the climate crisis is its impact on mental health. This study looks at this relationship in the Indian context, through a relatively unexplored perspective, by investigating the effects of nature connectedness (NC), pro-nature conservation behaviours (ProCoB) and geographical green cover (GGC) on mental health (MH) among middle-aged adults residing in India, and the existing inter-relationships. 180 middle-aged Indian adults, selected through purposive and snowball sampling, from across 21 states and 2 Union Territories (UTs), were administered questionnaires through a Google form. Their data was collected and scored, and the GGC was calculated for each state/ UT from the India State of Forest Report 2021. Correlation and Regression analysis were conducted on the scores using SPSS. A positive and statistically significant correlation exists between the variables NC, ProCoB and MH; NC, MH and GGC; and NC and ProCoB. NC and ProCoB predict MH. Gardening also predicts MH. The findings are new and contribute to the field of Environmental Psychology. It provides a scientific basis for the often romanticized relationship between man and nature as found in literature. It has great implications for the future, such as increasing awareness and understanding, and planning interventions to improve both environment and wellbeing. 2024 selection and editorial matter, Dr. Sundeep Katevarapu, Dr. Anand Pratap Singh, Dr. Priyanka Tiwari, Ms. Akriti Varshney, Ms. Priya Lanka, Ms. Aankur Pradhan, Dr. Neeraj Panwar, Dr. Kumud Sapru Wangnue; individual chapters, the contributors. -
Beyond the borders: Fashion influencers shaping global trends
Social media has emerged as a powerful platform that revolutionized the way the fashion industry operates. Fashion influencers have significantly impacted global consumer trends and brand perceptions with their large followings and engaging content. This chapter investigated the ways in which fashion influencers leverage social media platforms to shape consumer behavior, promote sustainable fashion practices, and bridge cultural boundaries to create a more inclusive fashion community across borders. This chapter has contributed to a better understanding of fashion beyond borders, social media influencers' role in transforming the fashion landscape, and their potential to influence positive change in the industry by conducting a comprehensive literature review. This chapter explores social media influencers' multifaceted roles in redefining fashion globally. 2024, IGI Global. All rights reserved. -
Influencing the influencers through co-creation: Approaches to successful brand strategies
In today's technology-driven landscape, the internet and social media have seamlessly woven themselves into the fabric of both brands and consumers' lives. Among the arsenal of modern marketing strategies, influencer marketing has emerged as a formidable force. It bestows organisations the privilege of accessing extensive and dedicated online influencers and co-creation as a technique, making it one of the most potent tools in their marketing toolkit. This chapter focuses on the intricate art of how brands strategically harness the power of social media platforms and influencers to extend their reach far and wide, aiming to connect with as many consumers as possible. By forging these connections, brands aspire to cultivate a devoted and unwavering fan base, fostering long-term customer loyalty. 2024, IGI Global. All rights reserved. -
Eradication of Global Hunger at UN Initiative: Holacracy Process Enriched byHuman Will and Virtue
The researchers have directed their attention to the UNs 2030 Agenda for Sustainable Development and its 17 Sustainable Development Goals (SDGs), with a specific focus on two critical objectives: hunger and poverty alleviation. While the UN has been vocal about eradicating hunger and poverty, the researchers believe that a fundamental shift in human perspective is needed. They propose a novel approach rooted in holacracy to revolutionize food production, distribution, and management. At the core of their proposal lies the ancient Indian principle, Vasudhaiva Kutumbakam, which translates to The World Is One Family. While it may seem utopian, the researchers see it as a reachable goal through holacracy. Their hypothesis centres on producing food for all and collectively utilizing it, transcending national boundaries and individual interests. The researchers advocate for a transformation in the way the UN operates by embracing holacracy as a practical social technology rather than a mere concept. Holacratic organizations, they argue, have the potential to remove barriers obstructing progress. The implementation of their vision begins with the UN functioning as a global nerve centre for data, with its 193 member nations acting as equal and interdependent contributors. This Centre would display the worldwide food landscape and foster a moral and ethical awakening, emphasizing the shared responsibility for all humanity. Real-time data on food availability, supply chains, and consumption would be accessible on a public website. Holacracy, they contend, should inspire individuals to prioritize love for humanity as a panacea. Power circles interconnect to collaboratively address issues. The UN could serve as a catalyst for this transformation. The knowledge nerve centre would provide critical data on arable land, water resources, and supply chain infrastructure to facilitate problem-solving at various levels. Timely responses and actions would be driven by the principles of holacracy and advanced digital technologies, addressing concerns hindering the achievement of UN goals. This data-driven approach, coupled with actionable plans, aims to eliminate food shortages and subsequently combat poverty and hunger worldwide. In conclusion, the researchers envision a future where holacracy and a shared sense of responsibility propel humanity towards ending hunger and poverty, with the UN playing a pivotal role as a catalyst for change and a provider of essential data and guidance. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Synergizing Humanity and Technology: A Human-Machine Collaboration for Business Sustainability in Industry 5.0
In the context of Industry 5.0, this paper emphasizes the crucial role of human-machine collaboration for sustainable business practices. It explores the need for a people-centric approach, recognizing the significance of the human workforce alongside advanced technologies. The study investigates three influential theoriesActor-Network Theory (ANT), Activity Theory, and Socio-Technical Systems Theory (STS)proposing a novel Socio-Technical Interaction Network (STIN) model that synthesizes their strengths. The STIN model views systems as intricate networks of diverse actors, both human and non-human, acknowledging their agency and interactions within socio-technical environments. By incorporating elements from each theory, it prioritizes contextual analysis, considering socio-cultural and environmental influences on human-technology interactions. The STIN model aims to provide a holistic lens for interdisciplinary research and guide the design of technology-infused systems aligned with human needs and societal contexts. In conclusion, human-machine collaboration is deemed not just a technological necessity but a strategic imperative for organizations striving for long-term sustainability in Industry 5.0, fostering adaptability, innovation, and sustainable practices. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Enhancing instructional effectiveness using the metaverse: An empirical analysis of the role of attitude and experience of participants
The Metaverse has been gaining importance, with businesses looking to adopt the same for processes rangingfrom onboarding to customer experience. The current study has been conducted to evaluate the impact of learner characteristics on motivation to participate in metaverse-based training programs across various organizations. Based on literature and theory, two main characteristics were identified: attitude towards the metaverse and experience with the technology. Data for the study was collected using a structured questionnaire and 103 responses were collected from employees belonging to various organizations in India. The analysis and interpretation of the data was done using statistical techniques through the tool of SPSS. The study found out that both the learner characteristics have a strong positive relationship with each other, and attitude towards metaverse has a stronger relationship with learner motivation than the experience of use. The findings suggest organizations focus more on the manner in which they should introduce metaverse at the workplaces and need to keep the employee attitude towards any kind of change; more of a technological change in mind when they are strategizing to implement metaverse-based training programs. 2024, IGI Global. All rights reserved. -
Impact of Multi-domain Features for EEG Based Epileptic Seizures Classification
Accurate detection and classification of epileptic seizures play a pivotal role in clinical diagnosis and treatment. This study introduces an innovative approach that leverages multi-domain features extracted from Electroencephalogram (EEG) data in conjunction with Supervised learning classification techniques. Initially, EEG data undergoes preprocessing through data standardization, followed by the extraction of essential features per instance, encompassing combination of Time domain, Frequency domain, and Time-Frequency domain features. These extracted feature combinations are subsequently fed into the machine learning-based boosting classifier Adaptive Boosting (ADABOOST) for an accurate and precise classification of epileptic signals. Validation of the proposed method is conducted using EEG data from the BEED (Bangalore EEG Epilepsy Dataset) and BONN (University of BONN, Germany) database to detect epileptic seizures. The experimental results show remarkably high levels of classification accuracy for various conditions: 99% accuracy for BEED data, 98% accuracy for BONN data for classifying seizures from healthy states, and 91% accuracy for classifying seizure onset from seizure events. Furthermore, the study applies the Gaussian Nae Bayes (GNB) classifier to differentiate various types of epileptic seizures, employing evaluation metrics such as the confusion matrix, ROC curve, and diverse performance measures. This method demonstrates significant potential in supporting experienced neurophysiologists decision in the clinical classification of epileptic seizure types. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Improving maternal health by predicting various pregnancy-related abnormalities using machine learning algorithms
Over the past few decades, artificial intelligence has been showing its high relevance and potential in a vast number of applications, particularly in the healthcare domain. Having a healthy pregnancy is one of the best ways to promote a healthy birth. Getting early and regular prenatal care improves the chances of a healthy pregnancy. Complications involved in the individual's pregnancy need to be predicted on time accurately. AI can help clinicians to make decisions by assisting them in decision-making. In this regard, the objective of this chapter is to provide a detailed survey of various pregnancy-related abnormalities; and to explore various machine learning algorithms to classify/predict pregnancy-related abnormalities with higher accuracy. A generic framework that focuses more on classifying various features into normal and abnormal, and to be monitored patients to provide support and care during an emergency. 2023 by IGI Global. All rights reserved. -
Magical mushroom Ganoderma-A Promising treatment for cancer
[No abstract available] -
Narratives of the self: Comments and confessions on Facebook
Narratives are structured around events, which are used to tell a story. The self is perpetually being constructed through narratives of experience. This chapter focuses on the phenomenon of Facebook confession pages and how they contribute to the construction of digital identity. Drawing on insights from my project on the role of Facebook College Confession pages, the chapter examines how these platforms have transformed the way users express and shape their identities. The anonymity provided by these pages allows users to post confessions without revealing their identities, encouraging a form of virtual self-exploration. These confessions, often written by nameless authors, generate a complex and ongoing narrative of identity, shaped by the interaction of multiple voices and viewpoints. The chapter also explores the motivations behind sharing personal confessions, even when the responses may be negative, and how this contributes to the perpetual construction of the digital self. By examining the intersection of public and private spheres in these online spaces, this chapter highlights how the breaking of the public-private divide enables users to create and negotiate their identities in a digital, networked world. The narrative constructed is endless, and the post is not an end in itself. It paves the way for the generation of an endless narrative by multiple authors with multiple viewpoints. This chapter explores the reasons behind sharing such posts on Facebook, even if the comments are negative in tone. It will refer to Anthony Giddens' concept of time-space "distanciation" (Keefer et al., 2019) to show how multiple tellers through their narratives help to build the complex networked identity of a user. The study will also analyse the role played by the breaking of the public-private divide in creating such spaces for the construction of a private self through public voices. 2024 Rimi Nandy.