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Introduction to blockchain for internet of things
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Biomass-derived carbonaceous materials: Synthesis and photocatalytic applications
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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. -
Improving organizational environmental performance through green training
It is necessary to equip employees with green abilities as well as to develop their dedication towards green behaviour in order to improve an organization's environmental performance. The purpose of this research is to evaluate the direct impact of green training on organizational environmental performance (OEP) and the mediating effect of organizational citizenship behaviour on the environment (OCBE). The study is based on responses from 107 employees of the IT sector in India. The findings suggest that green training has a significant positive impact on the organizational environmental performance and that the impact is strengthened by organizational citizenship behaviour towards the environment. The findings are of particular importance given the growing importance of sustainability in the organizational context. 2023, IGI Global. All rights reserved. -
Introduction: Tourism at a crossroads
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Integration of sustainability in business through finance
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Volatility Clustering in Nifty Energy Index Using GARCH Model
Volatility has become increasingly important in derivative pricing and hedging, risk management, and portfolio optimisation. Understanding and forecasting volatility is an important and difficult field of finance research. According to empirical findings, stock market returns demonstrate time variable volatility with a clustering effect. Hence, there is a need to determine the volatility in Indian stock market. The authors use Nifty Energy data to analyse volatility since the Nifty Energy data can to be used to estimate the behaviour and performance of companies that represents petroleum, gas, and power sector. The results reflect that Indian stock market has high volatility clustering. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Comparative Analysis of Different Machine Learning Prediction Models for Seasonal Rainfall and Crop Production in Cultivation
Agriculture is one of the strengths of India, from the last few years, gradually the agriculture growth is going downwards in other side the population growth is upwards. Reason for agricultural downward growth depends on so many parameters. The rainfall is one of the main parameters which affects the crop yield. Because of this, the farmers are also facing the loss. If they know this information in prior, the farmers can plan accordingly the type of crop suited for the particular season and it helps the farmer to get good profit out of it. Machine learning scientific and statistical methods are used for predicting the rain fall and crop yield. Kharif and Rabi are two seasons taken for analysis. The regressor predicting models are constructed to predict the seasonal rainfall and crop yield. This study primarily focuses on seasonal crop production prediction, which is dependent on rainfall. The different types of machine learning regression method are used to achieve better results. The performance of comparison models is evaluated using different metrics. Finally, the linear regression and Bayesian linear regression models comparatively produce the best result in terms of accuracy for rainfall prediction. The boosted decision tree regression model is achieving the better result for crop prediction. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Clustering Faculty Members fortheBetterment ofResearch Outcomes: A Fuzzy Multi-criteria Decision-Making Approach inTeam Formation
From a talent-pool of people, choosing an efficient team is tough. Faculty members of a higher education institution constitute the talent-pool. Teams have to be formed from them so that research output of each team is maximum. Amongst numerous research skills, thirteen are identified as most desirable skills. The level of these thirteen skills, viz., concept articulation, formatting according to templates/style sheets, identifying the relevant literature, initiative, logical reasoning, patience, problem formulation/problem finding, proof reading skills/identifying mistakes in written communication, searching/browsing skills/quick search techniques, sense of positive criticism, statistical knowledge, the ability to stay calm, and written communication skills, varies from person to person. Historical ranking of these skills and self-evaluation of the level of acquisition of these skills is used along with the years of experience, educational qualification, gender, marital status, etc., to rank individual faculty members. The fuzzy ranking of the faculty members thus obtained is used to cluster them into teams that are efficient in complementary skills. Each team thus formed is involved in collaborative research leading to research publication. The model is successfully implemented in a university department with 40 faculty members. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Conception of Blockchain Platform for Milk and Dairy Products Supply Chain in an Indian Context
The potential for adulteration in the Indian dairy supply chain process is immense. The possibility of incorrect information recorded by middlemen cannot be ruled out and found to be rampant. The reality is that the data required to assess the safety and quality of milk produced is inadequate in the existing setup. The current set of checks and balances to fight adulteration of milk and dairy products in India is studied and articulated. An elaborate and daunting set of procedures marks these checks and is still significantly found wanting. To increase the product's safety and traceability of the product an alternate pathway to deploy Blockchain technology in the milk and dairy product supply chain has been proposed. Despite the proposal requiring drastic changes in the milk and dairy industry, the authors believe the benefits of implementing a Blockchain platform far outweigh the challenges involved. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Artificial Intelligence-Monitored Procedure for Personal Ethical Standard Development Framework in the E-Learning Environment
The changes in the lifestyle of human beings due to the pandemic COVID-19 have affected all walks of human life. As a pillar of human development, the arena of education has a vital role to play in this changing world. The humongous and disruptive technologies that had made inroads into the educational scene as E-learning paved the way for ethical concerns in an unimaginable manner. Artificial intelligence is prudently incorporated for developing an ethical lifestyle for students all over the world. The Personal Ethical Standard Framework would work as a vaccine for the pandemic of the cancerous growth of the unethical habits of learners. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Blockchain and Its Integration in IoT
IoT devices have become an integral part of our lives. The world has witnessed an exponential growth in the number of IoT devices. Managing these devices and the data generated by them has become very crucial. Data security and users privacy are becoming more difficult as the number of devices grows. Blockchain, the technology behind Bitcoin, is known for data security and managing and efficiently maintaining huge amounts of data. Blockchain stores data in a chronological manner and in an immutable way. Integration of blockchain in IoT infrastructure has many advantages. This paper discusses various applications and challenges in blockchain. It highlights the adoption of blockchain in IoT infrastructure and reviews recent papers in this field. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
E-learning During COVID-19Challenges and Opportunities of the Education Institutions
As part of the COVID-19 lockdown, educational institutions were closed and adopted e-learning to keep the learning process going. Due to the COVID-19 pandemic, e-learning has become a required component of all educational institutions such as schools, colleges, and universities worldwide. This pandemic has thrown the offline teaching process into chaos. This chapter discusses the concept and role of e-learning during the pandemic and various challenges and opportunities of e-learning encountered by educational institutions. Three broad challenges identified in e-learning are inaccessibility, self-inefficacy, and technical incompetency. E-learning opportunities are no geographic barriers, flexibility, creativity, and critical learning incorporation increased utilization of online resources and reinforced distance learning. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Gamification in Education and Its Impact on Student MotivationA Critical Review
In education, gamification refers to including game characteristics and design ideas in the classroom setting. Over the previous five years, gamification has increased student motivation and academic performance. This study will examine the previous literature to see how gamification will disseminate over time, educational level (from nursery to college), causes, and the most frequently used game elements. A systematic literature review will search interdisciplinary databases for quantitative experimental studies examining educational gamification and providing information on current research lines. According to the findings of a comprehensive research study, gamification can be advantageous at all academic levels, from elementary school to college. Following systematic research, gamified learning can increase students motivation and intellectual accomplishment. Student learning may be made more pleasurable via gamification, which is the first advantage of this type of instruction. When used in the classroom, gamification can assist students who are weak in motivation and performing poorly academically. Because of the diversity of challenges and rewards that gaming parts provide, incorporating gaming elements into the classroom may serve as a motivational tool for students to learn. In the study's findings, students who enrolled in educational gamification courses were shown to be more interested and participatory than students enrolled in regular classrooms, on average. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Comparative Study of Machine Learning Techniques for Credit Card Customer Churn Prediction
A customer is a churner when a customer moves from one service provider to another. Nowadays, with an increasing number of severe competition with inside the market, essential banks pay extra interest on customer courting management. A robust and real-time credit card holders churn evaluation is vital and valuable for bankers to preserve credit cardholders. Much research has been observed that retaining an old customer is more than five times easier compared to gaining a new customer. Hence, this paper proposes a method to predict churns based on a bank dataset. In this work, Synthetic Minority Oversampling Technique (SMOTE) has been used for handling the imbalanced dataset. Credit card customer churn is predicted using random forest, k-nearest neighbor, and two boosting algorithms, XGBoost and CatBoost. Hyperparameter tuning using grid search has been used to increase the accuracy. The experimental result shows Catboost has achieved an accuracy of 97.85% and tends to do better than the other models. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Text Summarization Using Combination of Sequence-To-Sequence Model with Attention Approach
In daily life, we come across tons and tons of information which can be related to news articles or any kind of social media posts or customer reviews related to product. It is difficult to read all the content due to time constraint. Being able to develop the software that can identify and automatically extract the important information. There are two types of summarization methods. Extractive text summarization is the method where it picks the important content from the source text and gives same in the form of short summary, and on the other hand, abstractive summarization is the technique where it gets the context of the source text, and based on that context, it regenerates small and crisps summary. In this paper, we use the concept of neural network with attention layer to deal with abstractive text summarization that generates short summary of a long piece of text using review dataset. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
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. -
Forest Fire Prediction Using Machine Learning and Deep Learning Techniques
Forests are considered synonyms for abundance on our planet. They uphold the lifecycle of a diversity of creatures, including mankind. Destruction of such forests due to environmental hazards like forest fires is disastrous and leads to loss of economy, wildlife, property, and people. It endangers everything in its vicinity. Sadly, the presence of flora and fauna only increase the fire spread capability and speed. Early detection of these forest fires can help control the spread and protect the nearby areas from the damage caused. This research paper aims at predicting the occurrence of forest fires using machine learning and deep learning techniques. The idea is to apply multiple algorithms to the data and perform comparative analysis to find the best-performing model. The best performance is obtained by the decision tree model for this work. It gave an accuracy of 79.6% and a recall score of 0.90. This model was then implemented on front-end WebUI using the flask and pickle modules in Python. The front-end Website returns the probability that a forest fire occurs for a set of inputs given by the user. This implementation is done using the PyCharm IDE. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.