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Food Security and Its Impact on Society: Cases of Developing World
Food security is a matter of concern in the twenty-first century as is evident from the importance given to it in the United Nations Sustainable Development Goals. Despite attempts to address food scarcity concerns at global conventions such as the World Food Summit of 1996, food remains scarce. Scholars further suggest that though food scarcity is a global issue, its roots and impact is local. Consequently, a study of food must study the major challenges that converge to undermine food security worldwide including conflicts, climate change, global policies and in recent times even the Covid 19 pandemic. However, at a fundamental level food scarcity is the by-product of not just a legacy of past failures to build more just, sustainable, and resilient food systems, but rather a by-product of our inability to be responsible and sustainable consumers. This chapter highlights that despite surplus food production, developing nations often face food insecurity owing to the diversion of food towards developed nations. These nations, instead of sharing global resources (including food and agricultural labour), often contribute towards the global food crisis. Moreover, some of these developed nations engage in an industrialised system of food produc-tion which might meet the nations food requirements but are not sustainable modes of production and pose a serious threat to the environment. Nevertheless, the indis-cretions of the developed nations affect the developing nations economically as well as socially. As social outcasts, marginalised communities and individuals within the developing world are worst affected. As a result, this chapter offers insight into the social struggle brought on by inaccessibility to food. The chapter further suggests that addressing concerns of food security is not only a matter of addressing the inequalities manifest in the production, distribution and consumption of food but also learning to be responsible and sustainable consumers. Simply stated, the chapter recommends connecting SDG 2 with SDG 12. This chapter would also include the position of India in GHI, the Ukraine crisis and its aftermath in various developing countries, the earthquake in Turkey and how it affects the food security, and a few instances from Africa to highlight the concepts of food security and its correlation with sustainability of any society. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Forecasting Demand for Paddy and Cotton in India: Empirical Analysis Using Machine Learning Models
India has a thriving and varied agricultural sector, which has long served as the foundation of the economy. Agriculture contributes significantly to Indias economy and is essential to the nations food security because a sizable percentage of the countrys agricultural population works in farming and associated industries. Indian farmers have managed to successfully produce a variety of commodities, including cash crops like cotton and sugarcane as well as staples like rice and wheat, despite confronting numerous obstacles like small landholdings, poor infrastructure, and unpredictable weather. In this context, it is crucial to examine the status of Indian agriculture at the moment, its advantages and disadvantages, and the possibilities and difficulties confronting farmers and policymakers. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
Forecasting of Environmental Sustainability through Green Innovation of E-Vehicle Industry
E-mobility sustainability forecasting is getting more detailed with study, taking into account social cost in addition to technological, economic, or environmental factors. One solution for reducing greenhouse gas emissions is to implement green innovation in the transportation sector. The citizenrys view and acceptance of electric cars must be improved, more research into the social cost of these innovations is required. Consequently, the transportation industry might decarbonize more quickly. Another approach to do it is to advocate for more all-encompassing green innovations that can enhance sustainable development. Using Our Common Future, published in 1987 by the World Commission on Environment and Development [1], the commission emphasized the importance of sustainability while integrating social and economic development. Additionally, it recommended that governments take environmental factors into account while making decisions. The significance of sustainability was then increased and institutionalized, which meant that nations began passing laws that promoted sustainability. Consumer awareness of sustainability is rising largely from an economic and environmental standpoint. This also has an impact on the transportation industry and poses significant environmental, social, and economic difficulties. However, given that it generates close to 5% of the GDP and employs almost 11 million people, transportation is crucial from an economic standpoint. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
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. -
Forecasting the Stock Market Index Using Artificial Intelligence Techniques
If the stock market would have a predictable to maximum accuracy, then every stockbroker and investor would have been billionaire. But it is not the ground truth. In a one-to-one interaction with stock analysts, who mention that the stock market is unpredictable and that is why their role is important, else everything would have been black and white. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
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. -
Fostering civic engagement and community development through service-learning capstone courses in higher education: An in-depth analysis of department models in Indian universities
A nation's strength is intricately linked to the education of its citizens, and the evolving landscape of higher education is evident in the changing role it plays. The National Education Policy (NEP) established on July 29, 2020, provides a framework that opens avenues for experiential learning, emphasizing hands-on experiences to complement theoretical knowledge. Keeping this in mind, this chapter introduces the Service-Learning Capstone Course Model designed to cultivate civic responsibility, empathy, and risk management while fostering the holistic growth of learners as responsible citizens in this century. The study demonstrates how the inclusion of a service-learning component in the syllabus can develop personal, professional, and academic growth in a learner through the knowledge gained. 2024, IGI Global. All rights reserved. -
Fostering mindfulness and compassion: Strategies, benefits, and challenges
The integration of compassion, mindfulness, and service learning in higher education is emphasized in this abstract via an all-encompassing theoretical framework. Educators are assisted in the development of transformative learning experiences by utilizing service learning frameworks, compassion education models, contemplative pedagogy, transformative learning theory, and holistic education paradigms. Civic responsibility, self-awareness, and critical reflection are emphasized within the framework. By traversing this conceptual terrain, educators make a valuable contribution to the comprehensive growth of pupils, nurturing individuals who are conscientious, empathetic, and socially accountable, thereby equipping them to confront the intricacies of existence. 2024, IGI Global. -
Fostering Resilience and Well- Being: Integrating Mindfulness Practices in Educational Settings Amidst Crisis
The chapter specifies the structure and content of a comprehensive examination of integrating mindfulness practices into educational settings to promote resilience and well- being during times of crisis. It examines the fundamental concepts of mindfulness, its historical context in education, and the theoretical foundations supporting its application in educational settings. It explores the effects of various crises on education, highlighting the significance of innovative solutions to the challenges posed. It establishes a framework for discussing educationally tailored mindfulness practices supported by scientific evidence and real- world case studies. Strategies for incorporating mindfulness into curricula, overcoming obstacles, and training educators are concerned. It covers strategies for overcoming resistance and ensuring equity and accessibility. It concludes by highlighting future trends, providing recommendations for policymakers, educators, and administrators, and highlighting the enduring relevance of mindfulness practices during times of crisis. 2024 by IGI Global. All rights reserved. -
Fostering student engagement and empathy: The role of service learning in promoting mental health awareness and human rights advocacy
The chapter highlights the potential of integrating service learning into mental health and human rights curricula. It emphasizes the transformative impact of service learning in fostering student engagement, empathy, and social responsibility by blending theoretical frameworks, historical context, and practical models. Service learning emerges as a powerful tool for promoting positive change within communities and encouraging student activism on mental health and human rights issues. Advocating for ongoing exploration and implementation of service learning initiatives is crucial despite India's delayed implementation of the Mental Healthcare Act of 2017. Harnessing service learning's potential is essential for effectively addressing these critical issues. 2024, IGI Global. All rights reserved. -
Framework based on IoT, AI, and blockchain for smart access to government agricultural schemes
Agriculture plays an important part in most countries, such as India. A survey says that 54.6% of the total labor force of India is engaged in agriculture and its connected activities. The government is announcing many schemes to facilitate agriculture and support farmers. But most of the farmers are from poor families and are not able to reach the government schemes when they are really in need. Also, it is required to observe and measure the inter and intra-field variability in crops to enjoy the complete benefits of government schemes. This can be done with the advancements in the field of the Internet of Things. Information related to the impact of natural calamities on the agricultural field, malfunctions in the machinery used for cropping, yielding level, and health status of crops can be measured using the technology of IoT (Internet of Things) and analyzed using AI (Artificial Intelligence). Blockchain plays a critical role in replacing traditional means of data storage and exchanging agricultural data with a more trustworthy, immutable, transparent, and decentralized approach. By keeping all the transactions related to government schemes in blockchain, the possible crimes in the form of false data by the intermediate dealers acting between the farmers and the government can be addressed. This, in turn, allows useful government schemes to reach the farmer in time. We propose to develop a theoretical model using IoT, AI, and blockchain, which can assist the farmers in benefitting from the appropriate schemes announced by the government in time and achieving precise agriculture. 2024 Bentham Science Publishers. All rights reserved. -
Framework for a smart E-Procurement system for ship building
The research aims to improve the shipbuilding process by reducing the time required for building a vessel through adoption of lean in the procurement management process. The research identifies the AS-IS process for procurement, uses Value Stream Mapping to identify different actions, identifies the root causes for administrative lead time with the help of fish bone diagram and proposes a framework for e-procurement system. It was found that lack of proper communication and visibility between the processes can increase the lead time for purchase order creation for different materials. The use of a smart e-procurement system can improve the visibility of the process across various departments and with the suppliers. This can improve the efficiency of the shipbuilding process, reducing the time required for manufacturing a vessel. 2024 by IGI Global. All rights reserved. -
Fraud detection in the era of AI: Harnessing technology for a safer digital economy
Fraudulent activities have increased along with the new prospects of the digital economy's quick growth for both consumers and enterprises. Conventional techniques of fraud detection are insufficient to keep up with these ever-evolving fraudulent strategies. In this sense, machine learning (ML) and artificial intelligence (AI) have become potent instruments to prevent and detect fraud and guarantee the safety of online transactions. This study examines the function of AI and ML and shows how these technologies can spot irregularities and intricate patterns that would be challenging to find with conventional methods. The study includes various methods of AI-based fraud detection and analyses important ethical issues related to these practices. Furthermore, the study looks at developing technology and trends that will probably influence fraud detection in the future. In conclusion, the revolutionary potential of AI and ML in building a safer digital economy is analysed. 2024, IGI Global. All rights reserved. -
From automation to optimization: Exploring the effects of al on supply chain management
Automation and the integration of artificial intelligence (AI) are reshaping modern business operations. This evolution has historical roots, with a growing emphasis on efficiency and cost reduction. AI's transformative role in supply chain optimization is evident through key technologies and applications, which empower businesses to make data-driven decisions, enhance customer experiences, and reduce costs. Real-world examples illustrate how companies leverage AI to streamline operations and deliver products and services with precision. 2024, IGI Global. -
From bean to brain: Coffee, gray matter, and neuroprotection in neurological disorders spectrum
Coffee is a popular drink enjoyed around the world, and scientists are very interested in studying how it affects the human brain. This chapter looks at lots of different studies to understand how drinking coffee might change the brain and help protect it from neurodegenerative disorders especially like schizophrenia. With the help of available literature a link between the coffee mechanism and neurodegenerative disorders is established in this chapter. Researchers have found that drinking coffee can change the size of certain parts of the brain that control things like thinking and mood. Scientists also study how coffee's ingredients, especially caffeine, can change how the brain works. They think these changes could help protect the brain from diseases. This chapter focuses on how coffee might affect people with schizophrenia as hallucination is caused during and after excess consumption of caffeine. There's still a lot we don't know, but researchers are learning more by studying how different people's brains respond to coffee over time. Overall, this chapter shows that studying coffee and the brain could lead to new ways to help people with brain disorders. This study also draws ideas for future research and ways to help people stay healthy. 2024 Elsevier B.V. -
From Beans to Business: A Rise of Coffee Preneurs in Kodagu, Karnataka
Coffee is the world's third most consumed beverage after water and tea. India stands at the 7th position as the largest coffee exporter globally, with a significant contribution of 72.5% from Karnataka and 33% from Kodagu alone. This region plays a crucial role in the country's coffee industry, making it a vital component of India's economy, and 80% of the residents of Kodagu rely on coffee cultivation for their livelihood. Coffee farming is considered an annual crop that requires the generated income to be cycled to the subsequent year's coffee cultivation. Planters face numerous challenges during their production, which forces them to sell or convert their agricultural lands into concrete lands (buildings) or convert them into resorts, thereby changing their occupation, which makes coffee sustainability questionable. Therefore, coffee farmers have recently adopted an entrepreneurial approach to augment their income sources and support their livelihoods and occupations. This study aims to assess the key drivers of coffee farmers opting for entrepreneurial activities to assist coffee farming in Kodagu, Karnataka. This study has revealed that additional income, passion for farming, business skills, available resources, opportunity, satisfaction, innovation, creativity, unfair market prices, education, and socialising platforms are the key determining factors for coffee farmers to choose entrepreneurship. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
From commitments to actions: Towards impactful, decisive, and resolute impact investment
The many threats of climate change make it important for us as a society to prioritize sustainability and build a greener economy. While there may be initial costs associated with implementing environmentally friendly practices, the long-term benefits are immeasurable. Impact investments have the potential to generate significant profits and also allow investors to support innovative solutions aimed at addressing many ecological challenges. This study analyses the policies that are necessary for facilitating transformative investments while striving towards low GHG emissions, climate-resilient development, and conserving biodiversity along with essential ecosystem services. The authors delve into the efforts made by the Asian Development Bank towards climate change financing and its impact investments, exploring their strategies until March 2023 with an understanding of how these efforts have impacted the environment and also various economic sectors across Asia, and analyse ADB's investment approaches to gain insights on how they are achieving SDGs through their climate finance initiatives. 2024, IGI Global. All rights reserved. -
From data to decisions: Harnessing AI and big data for advanced business analytics
This chapter focuses on the idea of business analytics through AI and aims to address how AI has emerged as a powerful force in augmenting and replacing traditional human-computer interactions in the realm of business analytics. AI-powered analytics can uncover hidden patterns, detect anomalies, and automate decision-making processes, significantly augmenting the efficiency and accuracy of data analysis. Thus, the purpose of this chapter is two-fold. First, the chapter sheds light on business analytics, big data, and big data analytics through AI. It delves into the theories of machine and deep learning and their synergy with big data analytics. Secondly, the authors analyze a case study to substantiate our theory. ML-based prediction models using stock market data are developed to underline the significance of adopting AI-driven approaches for business analytics. 2024, IGI Global. All rights reserved. -
From resistance to readiness: Leveraging neuroscience perspectives for successful change management in the manufacturing sector
Change initiatives often encounter resistance from employees, impeding successful implementation. Leveraging insights from neuroscience can provide valuable guidance in navigating this resistance and promoting readiness for change. Social experiences in a work environment affect the brain positively or negatively. By understanding the brain's response to change, change managers can create a supportive environment and communicate accordingly. This study examines the impact of social experiences on readiness to change among employees in the manufacturing sector from a neuroscience perspective. SCARF is a neuroscience-based model that evaluates five dimensions of social experiences such as status, certainty, autonomy, relatedness, and fairness. This quantitative study is based on data collected from different manufacturing organisations. The results of this study provide insights into how change managers can address these social domains to promote successful change initiatives and improve employee readiness to change. 2023 by IGI Global. All rights reserved. -
Fruit Waste as Sustainable Resources for Polyhydroxyalkanoate (PHA) Production
Production of polyhydroxyalkanoate (PHA) using commercially available carbon sources like glucose or sucrose makes the bioprocess economically nonviable, thereby hindering its commercialization. As an alternative to this issue, inexpensive and easily available agro-industrial wastes are now being exploited as feedstock for PHA production. Fruit wastes are generally discarded as they are considered to be the non-product leftovers which do not have any economic value when compared with the cost of their collection and recovery steps for reuse. But through the use of appropriate technological applications, these wastes can be converted to valuable by-products, which can increase the value of the products much higher than the cost associated with recovery steps. By recycling and reprocessing the fruit wastes, they can be channeled into many applications, and thereby the amount of fruit wastes discharged into the environment can be completely reduced along with their detrimental effects. Large amounts of fruit wastes are produced by fruit-based industries. The waste products can be both solids and liquids, and these wastes are of high nutritional and biomass values for microorganism; thus their addition to waterbodies can make them highly polluted (high BOD or COD). These fruit-based wastes still have a promising potential for bioconversion into products of commercial importance or can be successfully exploited as cheap raw materials for industrial production of commercially important metabolites. This chapter deals with the strategies for production of PHA from fruit waste substrates, extraction and characterization of PHA, and their applications in diverse sectors. The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2021.