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Dynamics of motivation in online education: Theories,techniques, and mediating factors
Online education is a process where learners encompass various subject areas, disciplines, and degree programs via an internet connection rather than in person. Online learning has become an essential part of delivering flexibility in education. The objective of the book chapter is to create and improve the motivational environment during online classes. It guides students who lack the motivation to achieve their degrees and educational objectives through online education. Students often need more motivation to succeed in the online and face-to-face teaching process. This chapter will focus on identifying the motivational factors, including intrinsic and extrinsic, that are essential for improving students' participation in online education which enables them to understand the importance and necessity of motivation for achieving their goals and desired degrees in any mode of instruction. This chapter will provide them techniques and technology that researchers have proved to be effective and improve the self-motivation factor for students to succeed in all modalities. 2023, IGI Global. All rights reserved. -
Women on the Board of Indian It Companies: Are They Audible and Visible?
Gender disparity on the board of Indian IT companies is a continuing saga despite the Indian Companies Act, 2013 mandating at least one-woman director in the executive position of public listed companies. Women in India are leaders of varied sectors of businesses and on top leadership positions except in IT companies. This study has found that 14 out of 25 leading IT companies in India has, got not more than two women on the board of directors. It has also been found that the reasons for said nomination are due to the statutory compulsion to have women on board. Information technology companies are responsible for innovation, business growth, transformation and diversification. Strategic leadership is the key for IT companies to achieve the above-stated objectives. Inclusiveness in the economic reforms is possible when women are given adequate representation in entrepreneurship and leadership positions in all sectors of industries. This study aims at examining the causes of the inadequate representation of women in Indian IT companies. Paper has examined the following issues to analyse the above-stated proposition: (a) How far the Indian IT industry has contributed to the empowerment of Indian women? (b) Whether the employment terms and recruitment policies of IT companies are sufficient to ensure the security of tenure and promotion to women employees and do it incentives women employees contribution towards innovation in their respective companies? (c) What are the factors contributing to women taking up leadership positions in Non-IT Industries? (d) Whether family commitments are the reasons for women in the IT sector to decline leadership positions or whether male domination is a cause for women to be backward in IT companies leadership positions? (e) Should mandatory reservation of adequate percentage of seats for women in administration be uniformly applied also for employment of women in the IT sector and how far the practice followed in developed jurisdictions need to be incorporated under the Indian law? Enrolment of women in IT and business education is on par with their counterparts. Since women occupying leadership positions is negligible, the paper examines the challenges and proposes solutions to ensure gender equitable reforms in the leadership roles of Indian IT companies. Data related to board composition and shareholding patterns of Indian IT companies are looked into and analysed to identify whether women possess capital or management control in the Indian IT companies. To critique the role of women in other sectors of employment with that of the IT companies, data collected from the National Association of Software and Services Companies (NASSCOM) and Indian government-sponsored schemes are considered. The data are also collected from various sources such as Sustainability Reports of Wipro, Infosys, HCL, Dell, Accenture, Tata, Human Development Index (HDI), United Nations Department of Economic and Social Affairs (UNDESA). The data compiled reflect the factors that affect womens career progression in the Indian IT sector. This study has found that there is an absolute imbalance in terms of gender diversity on the boards of Indian IT companies. Reasons for the same are as follows: 1. Women who have excelled in technological education are not willing to take up leadership positions in IT companies due to the challenges and risks involved in this specific sector, 2. Family commitments and health issues are not conducive for women to dedicate the required time in managing corporate boards of IT companies, 3. Joint families and a patriarchal Indian system limits woman to undertake employment, 4. Women with liberal outlook and merit are not preferred as a choice by male leaders of IT companies due to the fact that they never want to be led by women, 5. The upskilling programmes organized by IT companies to their women employees are not sufficiently focused to promote women to leadership positions and 6. Excess share qualification for directorship prescribed by listed public companies is an impediment for women to be considered for executive positions. Paper suggests strategies and policies for the promotion of women employees to executive positions and ensuring the disclosure of diversity of corporate boards as a prerequisite to listing its shares. Secondly, it proposes to amend Companies Act, 2013 to prescribe a higher number of mandatory appointments of women on board to make it mandatory for women to be part of committees of the board mandated under the Companies Act. Thirdly, it proposes that the B-Schools admission policies should increase the intake of women candidates for management programmes so that they would possess the adequate competency to govern corporate boards of Indian IT companies. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Gucchi (Morchella esculenta)
This chapter focuses on Morchella esculenta as a nutraceutical and functional food, its habit, habitat, general characteristics, availability, biologically active compounds present and pharmacological and medicinal value. Mushrooms are spore-bearing fleshy fruiting bodies of fungus often present above the ground. Greeks and Romans included mushrooms in their diet. Romans considered mushrooms as the food of supernatural beings, despite the Chinese contemplating them as the elixir of the human being. Functional foods that are prepared from morel mushrooms are of high medicinal properties. The production of M. esculenta worldwide is 1.5 million tonnes of fresh weight and 150 tonnes of dry weight. India and Pakistan are the major morel-producing countries and each country has about 50 tonnes of dry morels. The pharmacological properties of Morchella species show its use in Chinese traditional medicine since 2, 000 years and in Malaysia and Japan to cure several diseases. 2023 Deepu Pandita and Anu Pandita. -
Robotics: challenges and opportunities in healthcare
Today, healthcare services and systems are becoming very complex and include a large number of entities characterized by shared, distributed and heterogeneous devices, sensors, and information and communication technologies. Various artificial intelligence techniques have been implemented in various sectors like smart cities, energy, IT sectors, banking, agriculture, retails, and many more, but it has been always challenging to demonstrate this technique effectively in healthcare sector due to its sophisticated procedure and its handling. Data analytics research on healthcare data has grown significantly over the past 10-12 years, and the execution of data analytics algorithms and systems in healthcare has been progressing more quickly. The data analytics service section has gained considerable attention with the development of technology, especially artificial intelligence robots, in the healthcare sector. Robots can help people with cognitive, sensory, and motor disabilities, help the sick or injured, support caregivers, and assist the clinical workforce. The purpose of this study is to provide historical evolution of robotics in healthcare with an overview of the influence of robots in healthcare like clinical support, patient transfer in hospitals, to handle heavy surgical instruments, to transport medical waste, for drug delivery, patient management etc. Furthermore, this chapter also covered the challenges and opportunities in healthcare and also offers a comprehensive aspect at how robots are incorporate in various healthcare applications. 2025 Elsevier Inc. All rights reserved. -
Youth and Media Literacy in the Age of Social Media
Living in the age of information means information is all pervasive, uncensored, unreliable, and with the potential to influence. The unfettered access to information and communication through social media is a double-edged sword in the hands of youth. The impact of this was explored from sociocultural and mental health perspectives. Specifically, the role of media literacy in combating the challenges posed by usage of social media was explored in this chapter. Various theories, frameworks, models, and components of media literacy were analysed. Impact of the various media literacy interventions on the youth, case studies of specific information literacy programs across regions, and other relevant critiques were reviewed and consolidated. Further to this, recommendations have been presented on creating robust in-school, and outside-school media literacy programs for the youth. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Big Data Analytics: A Trading Strategy of NSE Stocks Using Bollinger Bands Analysis
The availability of huge distributed computing power using frameworks like Hadoop and Spark has facilitated algorithmic trading employing technical analysis of Big Data. We used the conventional Bollinger Bands set at two standard deviations based on a band of moving average over 20 minute-by-minute price values. The Nifty 50, a portfolio of blue chip companies, is a stock index of National Stock Exchange (NSE) of India reflecting the overall market sentiment. In this work, we analyze the intraday trading strategy employing the concept of Bollinger Bands to identify stocks that generates maximum profit. We have also examined the profits generated over one trading year. The tick-by-tick stock market data has been sourced from the NSE and was purchased by Amrita School of Business. The tick-by-tick data being typically Big Data was converted to a minute data on a distributed Spark platform prior to the analysis. 2019, Springer Nature Singapore Pte Ltd. -
Computational techniques for sustainable green procurement and production
Computational techniques are used to generate, solve, analyze, explain, or manage any simple or complex task. The use of environmentally responsible techniques to meet demand for resources, commodities, utilities, and services is known as green procurement. Computational technique in green procurement and production is one of the components of sustainable procurement, along with a commitment to social responsibility and good corporate behavior. Some solutions for this kind of issue are low-maintenance, energy-efficient, and long-lasting. Several experts and researchers provided their findings on the environmental impact of ICT with the use of computational techniques. Also, the importance of energy-efficient information technology for environmentally conscious and feasible information technology is a hot topic because a computer faces environmental challenges at every stage of its life, from development to use to disposal. Due to changing environmental conditions, corporations have prioritized carbon emissions in procurement and transportation, which have the highest carbon impact. To encourage potential suppliers to adopt environmentally friendly practices, green criteria should be introduced into public procurement. Environmentally friendly corporate practices and environmental conservation are considered significant tools through public procurement. Techniques for green procurement and production procedures have recently been correlated with the concept of computational techniques of green procurement and production, owing to the increased emphasis on the concept of computational approaches. For eco-friendly procurement and production operations, computational approaches are inculcated and presented in the same way that they are for green procurement and manufacturing. From this perspective, this chapter presents a methodology for merging computational techniques into green procurement and production in public procurement in the form of green computing. 2024 by Elsevier Inc. All rights reserved, including those for text and data mining, AI training, and similar technologies. -
Occupancy Monitoring to Prevent Spread of COVID-19 in Public Places Using AI
The chapter aims to automate the counting of people for occupancy monitoring and send an alert email if the occupancy exceeds the defined threshold in case of restricted occupancy guidelines. The study aims to reduce the manual error, effort, and time for people counting and provide a tool for footfall analysis. We propose and implement an occupancy monitoring system by counting the number of people entering and exiting a building/room using cameras and machine learning (ML) algorithms. The Single Shot Detector (SSD) algorithm, which is based on the MobileNet architecture, is used. This project provides an effective process for execution using either a recorded video file or a live stream from a camera. As the system automates counting people, it reduces human effort and error. It provides accurate results on time. The project can be implemented anywhere using a laptop and a camera for capturing the video. Thus, it provides high portability of the project. The system can leverage pre-installed CCTV cameras and systems in colleges, malls, offices, etc. Thus, it requires less additional expenses and is economically friendly for the organization/decision-making authority. This chapter includes implications for various use cases such as ensuring adherence to COVID-19 guidelines by organizations, streamlining janitorial services, prevention of stampedes, improving indoor air quality, improving electricity efficiency, etc. This project fulfills an identified need to automate the people counting process and generate alerts accordingly. 2025 by Apple Academic Press, Inc. -
Application of neuroscience methods in HRDM for brain-based human capital optimization
For years, human resource development and management (HRDM) has used behavioral assessments to gauge employee potential. However, advancements in cognitive behavioral neuroscience (CBN) have opened up new possibilities for understanding how the human mind works. This chapter explores the practical applications of neuroscience methods like EEG, ERP, MRI, and fMRI, as well as neurofeedback and biofeedback, in talent identification, leadership development, and employee well-being. Importantly, these insights can be directly applied in HRDM practices, leading to more effective talent management, leadership development, and improved employee well-being. While recognizing the ethical considerations involved with these technologies, the chapter presents a compelling vision for a future where HRDM practices are informed by a deeper understanding of the brain, enabling the workforce to reach its full potential. 2024 by IGI Global. All rights reserved. -
Sustainable materials for urban streets: trends, challenges, and case studies
Urban planners face a growing need for efficient, smart, and sustainable projects. One of the dynamic urban elements of cities is its streets, which accommodate the majority of the public realm. This study aims to identify sustainable materials that are employed in the construction of urban streets and analyze the potential for other sustainable materials in future street design. We conduct a thorough literature review through case studies and identify sustainable materials currently in use in the construction of urban streets across the world. This study focuses on existing and potential sustainable materials for urban streets suitable for Qatar. Hence, the objectives of this study are: (1) to identify sustainable materials in the construction of urban streets; (2) to analyze challenges to using sustainable materials in making urban streets more sustainable; (3) comparative analysis of the case studies. The study concludes with sustainable urban street design guidelines derived from Qatar. 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Forecasting Stock Market Indexes Through Machine Learning Using Technical Analysis Indicators and DWT
In recent years, the stock market prices have become more volatile due to refinement in technology and a rise in trading volume. As these seemingly unpredictable price trends continue, the stock market investors and consumers refer to the security indices to assess these financial markets. To maximise their return on investment, the investors could employ appropriate methods to forecast the stock market trends, taking into account the nonlinearity and nonstationarity of the stock market data. This research aims to assess the predictive capability of supervised machine learning models for the stock market regression analysis. The dataset utilised in this research includes the daily prices and additional technical indicator data of S&P 500 Index of US stock exchange and Nifty50 Index of Indian stock exchange from January 2008 to June 2016; both the indexes are weighted measurements of the top companies listed on respective stock exchanges. The model proposed in this research combines the discrete wavelet transform and support vector regression (SVR) with various kernels such as Linear, Poly and Radial basis function kernel (RBF) of the support vector machine. The results show that using the RBF kernel on Nifty 50 index data, the proposed model achieves the lowest MSE and RMSE error during testing are 0.0019 and 0.0431, respectively, and on S&P 500 index data, it achieves 0.0027 and 0.0523, respectively. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Mobile-Based Indian Currency Detection Model for the Visually Impaired
According to surveys held in 2019, India holds the largest population standing just after China, but when it comes to visually impaired people, India ranks number one. There are approximately 37 million people across India who are suffering from visual impairment. Special care and measures are taken to help these people live a peaceful life as any other citizen of India, but with the demonetization that happened in the recent years, the Indian economy was replaced with newer currency notes as an attempt to stop black money and fight corruption. Even though the objectives were clear and attainable, with the newer currency notes, the visually impaired people are facing various problems, as there is no provision for them to actually check the currency as the notes are not equipped with Braille system and the sizes of each and every currency is also the same in many cases. To counteract this problem, a mobile-based Indian currency detection model would be a better solution as it enables a visually impaired person to identify the value of specific currency he is holding. The mobile-based Indian currency detection model is the proposed model which will be using image processing for feature extraction and a basic CNN (convolutional neural network) for identification of currency with the given feature inputs. This model is being made into a mobile-based application so as to enable a visually impaired person to check for any possible frauds as fast as possible. 2020, Springer Nature Switzerland AG. -
An in-depth investigation into financial literacy levels in Indian households
In a complex financial world, lack of awareness complicates money management and savings. Emphasizing financial literacy is vital for informed decision-making. This study explores global financial illiteracy, advocating international initiatives. In India, it assesses disparities and government activities and reviews tax-saving and mobile banking. Gaps include limited studies on Indian households, necessitating gender-specific analyses and research on education's impact. The methodology outlines justification, operational definitions, and data collection techniques. With ANOVA and descriptive statistics on 285 respondents, the study reveals demographic analysis, indicating higher financial literacy with age and a gender gap. Education. positively correlates with financial literacy. Recommendations include interventions like financial seminars, collaboration with regulators, and destigmatizing money talks at home to enhance financial literacy and bridge gaps. 2024 by IGI Global. All rights reserved. -
Role of ICT in economic empowerment of women by being an effective facilitator for women entrepreneurship
Information and communication technology (ICT) is steadily gaining dominance over other channels as a standalone medium for gaining and sharing knowledge, hybrid working environment, network strengthening and funding, business collaborations, new venture set-up, marketing and branding. ICT being most effectively featured with accessibility and omnipresence has been capable of empowering a lot of developing and talent-rich areas, and women empowerment is one among them. This chapter makes an attempt to bring out the efficient role played by ICT in enhancing the lifestyle of women. It proposes to provide a detailed description of how ICT has empowered women, and entrepreneurs, to set up and develop their business ventures giving them access to required resources and making them more competent through information and wider access to the market. This chapter presents its findings based on a systematic review of different case analyses by using secondary data. The findings will be also supported by the evidence and information gathered from credible reports, articles, and publications. 2023, IGI Global. -
A Comparison of Similarity Measures in an Online Book Recommendation System
To assist users in identifying the right book, recommendation systems are crucial to e-commerce websites. Methodologies that recommend data can lead to the collection of irrelevant data, thus losing the ability to attract users and complete their work in a swift and consistent manner. Using the proposed method, information can be used to offer useful information to the user to help enable him or her to make informed decisions. Training, feedback, management, reporting, and configuration are all included. Our research evaluated user-based collaborative filtering (UBCF) and estimated the performance of similarity measures (distance) in recommending books, music, and goods. Several years have passed since recommendation systems were first developed. Many people struggle with figuring out what book to read next. When students do not have a solid understanding of a topic, it can be difficult determining which textbook or reference they should read. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Dandelion Algorithm for Optimal Location and Sizing of Battery Energy Storage Systemsin Electrical Distribution Networks
This paper describes a new way to improve the performance of an EDN by integrating distributed battery energy storage systems (BESs) in the best way possible. This method is based on the Dandelion Algorithm (DA). The search space for BES locations is first predetermined using loss sensitivity factors (LSFs), and then DA is used to determine the optimal locations and sizes. The reduction of real power distribution loss is regarded as the primary objective function, and the impact of BESs is extended to examine the network voltage profile, voltage stability, and GHG emissions. IEEE 33-busEDN is used to calculate the computational efficiency of LSF-DA. Results show that DA is more efficient than Archimedes optimization (AOA), future search algorithm(FSA), pathfinder algorithm(PFA), and butterfly optimization algorithm(BOA) algorithms. Furthermore, the results show that the proposed DA enhances all technological and environmental factors and RDN performance. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Identifying Wage Inequality in Indian Urban Informal Labour Market: A Gender Perspective
This chapter elucidates the wage differential between male and female informal workers in urban labour market by using employment and unemployment survey 61st (2004-2005) round, 68th (2011-2012), and Periodic Labour Force Survey 2019-2020 data of National Sample Survey Office (NSSO) unit level data. This study found that gender inequality not only increased during getting job but also persists after getting job during wage distribution. Based on the Oaxaca-Blinder (OB) decomposition, it is revealed that gender wage inequality is more in the labour market due to the labour market discrimination, that is, unexplained components. Hence, this study helps researcher, policy makers and government to fix the gender wage discrimination issues exist in the Indian labour market. This will enhance economic growth through the rise of the women labour force participation. 2024 A. Vinodan, S. Mahalakshmi, and S. Rameshkumar. -
A predictive model on post-earthquake infrastructure damage
Disaster management initiatives are employed to mitigate the effects of catastrophic events such as earthquakes. However, post-disaster expenses raise concern for both the government and the insurance companies. The paper provides insights about the key factors that add to the building damage such as the structural and building usage properties. It also sheds light on the best model that can be adopted in terms of both accuracy and ethical principles such as transparency and accountability. From the performance perspective, random forest model has been suggested. From the perspective of models with ethical principles, the decision tree model has been highlighted. Thus, the paper fulfills to propose the best predictive model to accurately predict the building damage caused by earthquake for incorporation by the insurance companies or government agency to minimize the post-disaster expenses involved in such catastrophic event. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. -
Denial of Service Attacks in the Internet of Things
A DoS attack is the most severe attack on IoT and creates a crucial challenge for the detection and mitigation of such attacks. A DoS attack occurs at multiple layers of the IoT protocol stack and exploiting the protocol vulnerabilities disrupts communication. Traditional mechanisms employ single-layer detection of DoS attacks, which individually detect and mitigate attacks. However, it is essential to establish a general framework for detecting DoS attacks in a real-time environment and coping with diversified applications. This can be achieved by fetching attack features of multiple layers to create a pool of numerous attacks and then designing a system that detects the attack when fed with specific attack features. This chapter comprehensively analyzes the research gap in the DoS attack detection techniques proposed. Secondly, we offer a two-stage framework for DoS attack detection, comprising Fuzzy Rule Manager and Neural Network (NN), to detect cross-layer DoS attacks in real time. The Input Data Type (IDT) is derived using a fuzzy rule manager that can identify the type of input dataset as usual or attack in real time. This IDT is passed to the NN along with the real-time dataset to increase detection accuracy and decrease false alarms. 2024 selection and editorial matter, Vinay Chowdary, Abhinav Sharma, Naveen Kumar and Vivek Kaundal; individual chapters, the contributors. -
Overview of Cyber Security in Intelligent and Sustainable Manufacturing
With the advent of the Internet of Things (IoT), a new transformation is predominant in the manufacturing industry, termed Industry 4.0. The revolution of IoT with artificial intelligence, Web3, robotics, and automation has transformed the traditional manufacturing system into a smart manufacturing system (SMS) by adding an intelligent component capable of automatic data collection through using sensors, processing data autonomously, and controlling machines remotely. However, adding automated intelligence, autonomous systems, and real-time data processing presents an insecure surface to cyber attackers to penetrate these cyber-physical systems (CPSs) and cause physical damage. This chapter presents a detailed discussion of cyber threats and incidents in the intelligent manufacturing industry, along with the available acceptable mitigation strategies. A taxonomy of cyber attacks on intelligent manufacturing systems clearly shows the difference between information technology threats and smart manufacturing cyber-threats. A detailed discussion on the limitations of SMSs in implementing cyber security is presented. Finally, some innovative machine learningbased security mechanisms (ML-based intrusion detection systems) are discussed that promise to detect anomalies/intrusions in such systems. 2025 selection and editorial matter, Ajay Kumar, Parveen Kumar, Yang Liu, and Rakesh Kumar.