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Farm food and beverage: An attractive element of gastronomy in agritourism
The admixture of agriculture and tourism creates new fields of area like agritourism. The primary activity of agritourism is providing unique agritourism attractions to the visitors. Among the interests, farm food and beverages act as substantial components that intrigue the visitors. Food gastronomy is connected with farm food and beverage and its inception. Tourists in the agritourist destination want to explore the culinary practices there. Hence, this book chapter provides an idea of the concepts of agritourism and gastronomy, the applications of gastronomy in agritourism, the significance and dimensions of farm food and beverage in agritourism, factors influencing travelers' food choices, the benefits of gastronomy in agritourism and the value-added advantage of gastronomy in agritourism. Food is always a determinant element of the quality of service in the tourist place. 2024, IGI Global. All rights reserved. -
Farming Futures: Leveraging Machine Language for Potato Leaf Disease Forecasting and Yield Optimization
Crop yield prediction is of paramount importance in modern agriculture. It serves as a linchpin for ensuring food security, efficient resource management, risk mitigation, environmental sustainability, and socioeconomic development. Accurate predictions enable us to maintain a stable food supply, optimize resource allocation, and manage the uncertainties associated with climate and market fluctuations. By fostering sustainable farming practices, crop yield prediction also plays a crucial role in reducing environmental impact and promoting rural development. Integrating artificial intelligence (AI) and machine learning (ML) in modern agricultural practices offers the potential to revolutionize the way we produce food, making it more sustainable, efficient, and resilient. This study has demonstrated the effectiveness of convolutional neural networks (CNNs) in the classification of potato leaf disease, achieving remarkable results with a test loss of 0.0757 and a test accuracy of 0.9741. 2024 Taylor & Francis Group, LLC. -
Faulty Node Detection Using Vertex Magic Total Labelling in Distributed System
Distributed system consists of huge number of nodes that are connected to a network, which is mainly intended and predominantly used for information sharing. Large users are prone to share data through the network and the stability and reliability of the nodes are remaining as the major concern in this system. Therefore, the inconsistent message transmission causes the nodes in the network to act differently, which would not be acceptable. A rapid method of malfunctioning nodes detection can improve the QoS of distributed computing environment. In this paper, a novel algorithm is proposed based on the calculation of vertex magic total labelling (VMTL) value for each and every node in the network. Upon receiving the message from the sender node, the receiver node will quickly detect the faulty node by comparing the VMTL pivot value (Pv). Experimental results show that the proposed approach leads to high true fault rate (TFR) detection accuracy compared to the false fault rate (FFR) detection. Finally, all the information related to the faulty nodes will be sent to the server node for further investigation and action. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021. -
Feature extraction and diagnosis of dementia using magnetic resonance imaging
Dementia is a state of mind in which the sufferer tends to forget important data like memories, language, etc.. This is caused due to the brain cells that are damaged. The damaged brain cells and the intensity of the damage can be detected by using Magnetic Resonance Imaging. In this process, two extraction techniques, Gray Level Co-Occurrence Matrix (GLCM) and the Gray Level Run-Length matrix (GLRM), are used for the clear extraction of data from the image of the brain. Then the data obtained from the extraction techniques are further analyzed using four machine learning classifiers named Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Random Forest (RF), and the combination of two classifiers (SVM+KNN). The results are further analyzed using a confusion matrix to find accuracy, precision, TPR/FPR - True and False Positive Rate, and TNR/FNR - True and False Negative Rate. The maximum accuracy of 93.53% is obtained using the GLRM Feature Extraction (FE) technique with the combination of the SVM and KNN algorithm. 2023, Bentham Books imprint. All rights reserved. -
Feature films as pedagogy in higher education: A case study of Christ University, Bengaluru
Contemporary education system in India was initiated by the British for the maintenance of their imperial administration. After India became an independent country, conscious efforts were made to overhaul the educational system to produce proper administrators and contributors for Indian polity, economy and culture. To assess dynamics of Indian education, various committees and commissions were formed. It also meant change in education programs, curricula and syllabi to meet national needs and global challenges. Most universities in India have limited infrastructure, thus the role of private or deemed to be university becomes crucial. Christ University attending to the social structure, internationalization and employability demands, offers a number of quality educational programs to ensure employable graduates. This has led the way in devising pedagogy and curricula to align with the global higher education practices. Here we discuss the use of commercial feature film as a pedagogical tool in the classrooms within the Deanery of Humanities and Social Sciences and its implication. 2018, IGI Global. -
Feature selection/dimensionality reduction
In today's world, medical image analysis is a critical component of research, and it has been extensively explored over the last few decades. Machine learning in healthcare is a fantastic advancement that will improve disease detection efficiency and accuracy. In many circumstances, it will also allow for early detection and treatment in remote or developing areas. The amount of medical data created by various applications is growing all the time, creating a bottleneck for analysis and necessitating the use of a machine learning method for feature selection and dimensionality reduction techniques. Feature selection is an important concept of machine learning since it affects the model's performance and the data parameters you utilize to train your machine learning models to have a big influence on the performance. The approach of minimizing the number of inputs in training data by reducing the dimension of your feature set is known as dimensionality reduction. Reduced dimensionality aids in the overall performance of the machine learning algorithms. 2023 River Publishers. -
Feature Subset Selection Techniques with Machine Learning
Scientists and analysts of machine learning and data mining have a problem when it comes to high-dimensional data processing. Variable selection is an excellent method to address this issue. It removes unnecessary and repetitive data, reduces computation time, improves learning accuracy, and makes the learning strategy or data easier to comprehend. This chapterdescribes various commonly used variable selection evaluation metrics before surveying supervised, unsupervised and semi-supervised variable selection techniques that tend to be often employed in machine learningtasks including classification and clustering. Finally, ensuing variable selection difficulties are addressed. Variant selection is an essential topic in machine learning and pattern recognition, and numerous methods have been suggested. This chapter scrutinizesthe performance of various variable selection techniques utilizing public domain datasets. We assessed the quantity of decreased variants and the increase in learning assessment with the selected variable selection techniques and then evaluated and compared each approach based on these measures. The evaluation criteria for the filter model are critical. Meanwhile, the embedded model selects variations during the learning model's training process, and the variable selection result is automatically outputted when the training process is concluded. While the sum of squares of residuals in regression coefficients is less than a constant, Lasso minimizes the sum of squares of residuals, resulting in rigorous regression coefficients. The variables are then trimmed using the AIC and BIC criteria, resulting in a dimension reduction. Lasso-dependent variable selection strategies, such as the Lasso in the regression model and others, provide a high level of stability. Lasso techniques are prone to high computing costs or overfitting difficulties when dealing with high-dimensional data. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Female entrepreneurship: Challenges faced in a global perspective
Women being employees is a very appreciative aspect. But women being employers is a bold and massive decision that they make, considering their busy life schedule, which traditionally includes looking after their families and themselves. This book chapter aims to identify the diverse challenges female entrepreneurs face, which could be in the context of society, structure, or finance. Identifying and vocalizing these challenges faced by these emerging entrepreneurs is inadequate, but tackling them is equally called for. This study provides a framework and scope for further research to look into more opportunities and measures to tackle these roadblocks. Last but not least, this book chapter anticipates inspiring all women and driving them to explore the essence of entrepreneurship. 2023, IGI Global. All rights reserved. -
Female masculinities and women of third nature: Analyzing the gender and sexual politics of identity and visibility of alternative masculinities through indian mythologies and literary narratives
Alternative sexualities have been a part of the Indian past since time immemorial, and mention of them is often visible in Sanskrit mythological texts. As much as the presence of hijras and other gendered cultural identities is in Indian and Western public discourses, there is a narrow space occupied by women of the third kind with female masculinities, with scant attention leading to the higher invisibility of women of the third kind. Female masculinity is often considered a "rejected shred, " while male masculinity is seen as real and heroic. This chapter focuses on "masculinity without men" to explore alternative masculinities-the concept popularized by Judith Halberstam (Judith Halberstam, Female Masculinity. Zubaan Books, New Delhi, 1998). We delve into the politics of alternative modes of enactment and production where male masculinity is embedded. This chapter centers on female masculinity and alternative forms of masculinities performed, enacted, and embodied by female individuals as reflected in the Indian past and mythology. This chapter further delves into identifying histories and representations of female masculinities in Indian literature to bring female masculinities and women of the third kind into academic discourse. Springer Nature Switzerland AG 2022. All rights reserved. -
Filmic afterlives: Considerations on the uncanny
[No abstract available] -
Financial Vulnerability in Households: Dissecting the Roots of Financial Instability
The phenomenon of household financial vulnerability, defined by unexpected shocksin income and expenditures, carries major implications for both individual households and the overall economy of a nation. For a considerable time, household debt has been widely acknowledged as the primary determinant of household financial vulnerability. This study aims to extend the analysis beyond the scope of household debt. Middle-income households may experience financial difficulties when faced with unexpected changes in income and expenses. These challenges can arise from several circumstances, including the inability to engage in discretionary activities such as dining out or vacations. For a very long time, it has been posited that low-income households exclusively experience financial vulnerability. Hence, it is imperative to thoroughly examine the concept of household financial vulnerability and its underlying factors to enhance households' ability to withstand adversities and better clarify the matter. In light of the prevailing economic recession triggered by the global pandemic and the ongoing confrontation between Russia and Ukraine, the significance of the matter is further underscored. This study aims to comprehensively define household financial vulnerability and examine its relationship with financial capability, digitalized payments, financial stress, and financial socialization. The current study anticipates establishing a foundational framework for future research endeavors in this specific field. Moreover, this paper also explores potential avenues for future research. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
FinTech in India: A systematic literature review
India is the second-most populous country in the world, with a rapidly growing economy. Its population is highly tech-savvy and has a high level of adoption of digital technologies. The Indian government has taken several initiatives to promote digital transactions and financial inclusion. These initiatives have been instrumental in the growth of fintech in India. Fintech, or financial technology, is transforming the financial sector worldwide. Fintech solutions have led to the creation of new business models, streamlined operations, and enhanced customer experience. India is no exception to this trend, as it has witnessed a significant growth in fintech in recent years. The fintech ecosystem in India is highly diverse, consisting of startups, technology companies, banks, and non-banking financial companies (NBFCs). There are various challenges faced by fintech companies in India, such as lack of access to capital, regulatory hurdles, and competition from established players. This chapter proposal aims to provide a basic literature review on the development of fintech in India. 2023, IGI Global. All rights reserved. -
FISCAL DECENTRALIZATION IN INDIA AND CHINA: Experiences in service delivery
[No abstract available] -
FloodWatch: Suggesting an IoT-Driven Flood Monitoring and Early Warning System for the Flood-Prone Cuddalore District in the Indian State of Tamilnadu
Floods continue to pose significant threats to communities worldwide, causing loss of life, property damage, and disruption of vital services. Timely and accurate flood monitoring and early warning systems play a critical role in mitigating these impacts. This chapter presents FloodWatch, an innovative IoT-based flood monitoring and early warning system designed to enhance community resilience and response capabilities for the Cuddalore district, classified as one of the multi-hazard-prone districts of Tamilnadu. The Cuddalore district has a coastal line of 68 km, hence it is vulnerable to cyclones, and heavy rainfall, in turn causing floods. FloodWatch leverages the power of the Internet of Things (IoT) technology and provides real-time data collection, analysis, and dissemination for flood-related parameters. FloodWatch integrates a network of smart sensors strategically deployed in flood-prone areas, including rivers, streams, and urban drainage systems. These sensors continuously measure key variables, such as water level, rainfall intensity, weather conditions, and soil moisture content. The collected data is transmitted to a centralized cloud-based platform, where advanced data analytics and machine learning algorithms are employed to process and analyze the information. FloodWatch utilizes historical data and predictive modeling to assess the risk of flooding and generate accurate early warnings. Through intuitive interfaces and mobile applications, relevant stakeholders, including local authorities, emergency responders, and residents, receive real-time alerts and notifications, enabling timely decision-making and appropriate response actions. Key features of FloodWatch include its scalability, adaptability, and user-friendliness. The system can be easily customized to cater to different geographical and environmental conditions, ensuring its applicability in diverse regions. Additionally, FloodWatchs intuitive interfaces provide actionable insights in a visually comprehensible manner, facilitating effective communication and community engagement. The implementation of FloodWatch offers several notable benefits, including improved flood preparedness, reduced response time, and enhanced disaster management. By equipping communities with the tools to monitor, predict, and respond to floods, FloodWatch contributes to minimizing the impact of flood-related disasters, ultimately fostering greater resilience and safeguarding lives and property. FloodWatch represents a significant advancement in flood monitoring and early warning systems, harnessing IoT technology to provide accurate and timely information to communities at risk. This chapter highlights the architecture, functionality, and advantages of FloodWatch, underscoring its potential to enhance resilience and contribute to more effective flood management strategies on a global scale. 2025 selection and editorial matter, A. Daniel, Srinivasan Sriramulu, N. Partheeban, and Santhosh Jayagopalan; individual chapters, the contributors. -
Flow Cytometry Analysis of In Vitro Induced Polyploidy in Plants
Polyploidy is the condition of having more than two sets of chromosomes. The mechanism of polyploidy helps in deriving special traits like an increase in biomass, an increase in the size of various organ systems, and secondary metabolite content for the progeny. Various chemical compounds (colchicine, trifluralin, and oryzalin) that have the capacity to alter the mitotic cycle were used for the purpose of inducing polyploidy. Various techniques, such as counting of chromosome number, chloroplast number, determination of pollen diameter, and estimation of leaf stomatal density and size, were developed to analyze the polyploidy of the plants. However, these methods are not reliable for their regular use. Thus, of all the above-mentioned approaches, the estimation of ploidy level by flow cytometry (FCM) has been the most popular over the last few decades. Flow cytometry is now extensively used for the verification of haploidy, aneuploidy, and polyploidy. The ease of sample preparation, fast acquisition, and accurate measurements have made the method popular in the domains of plant cell biology, systematics, evolution, genetics, and biotechnology. The current chapter discusses the induction of polyploidy and its importance in plant breeding. It also emphasizes the importance of FCM in the analysis of polyploidy and enumerates the various polyploidy studies involving the application of FCM. 2023, Bentham Science Publishers. -
Fluorescent carbon nanoparticle hybrids: synthesis, properties and applications
The development of materials in nanoscale morphologies with novel compositions is one of the major focuses of nanoscience and technology, as these materials are imbibed with unique properties that make them suitable for specific applications in a large variety of fields. Combining two or more chemically distinct constituents into a single nanostructure helps to attain desirable attributes of physical and chemical responses that can be efficiently utilized for specific applications. Hybrid nanomaterials constituted as a combination of multiple components into single nanostructures are known to showcase the properties of the individual components in tandem or synergy. Novel functionalities are also known to arise from integrating Fluorescent carbon nanoparticles (FCNPs) with other counterparts. FCNPs, when combined with other materials to form nanohybrids, provide copious functional attributes due to their inherent properties and the augmentation in properties due to the presence of the other materials. Integrating hybrid counterparts with FCNs improves the functional properties, which can be utilized for various applications such as photocatalysis, bioimaging, bio/chemo sensing, and many more. Herein we present an overview of recent and relevant works related to the synthesis, properties, and applications of fluorescent carbon nanoparticle (FCNP) hybrids. Various synthetic routes of FCNP hybrids via physical and chemical methods are summarized. The properties of the hybrid systems and the influence of hybridization on the properties are discussed. Applications of FCNP hybrids in various fields are also discussed in detail. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
Fluorescent carbon nanoparticles for catalytic and photocatalytic applications
In the present times, catalysis is ubiquitous in chemical processes. Catalysts range from macromolecules consisting of enzymes to nanoparticles, including metals/metal oxides and composite materials. Due to their harmlessness, biocompatibility, high stability, versatility, and ease of functionalization, carbon nanomaterials (CNMs) which are fluorescent in nature, are used extensively for catalytic applications. Several studies regarding the catalytic applications of CNMs have been reported. These applications range from homogeneous to heterogeneous catalysis, where CNMs are used as supports for metal/metal oxide nanoparticles. Extensive studies on nanocomposites, doping strategies, and their utility in catalysis have been carried out. Carbon-based electrocatalysts find applications in both storage and conservation of energy. The exceptional properties of these materials make them an apt choice for various environment-friendly organic transformations. Photocatalysis is another area in which CNMs have excelled. Photoluminescence, photostability, and electron transfer properties of CNMs make them potent candidates for several photoinduced reactions. Various CNMs, namely graphene, carbon dots, nanotubes, graphitic carbon nitride, fullerenes, and graphdiyne, find applications in medicine, catalysis, sensing, bioimaging, supercapacitors, and many more. This chapter focuses on the catalytic and photocatalytic applications of CNMs. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
Fluorescent Photosensitizers: A Promising Tool for Biomedicine
The growing demand for the detection for biomedical imaging has taken the interest of researchers as there is a significant increase in cancer and malignant diseases across the globe. Photosensitizers assisted with fluorescent properties can be a pioneer in this field. Photosensitizers generally damage the living cell, however, selected fluorescent photosensitizers can offer a minimal threat to the living cells. Medically relevant processes such as live cell imaging and photodynamic therapy can be monitored using this technique. Some of the commonly used fluorescent photosensitizers include porphyrins, chlorins, and bacteriochlorins. This chapter addresses the significance, limitations, and future perspectives of fluorescent photosensitizers in biological applications. Scientists can develop efficient fluorescent photosensitizers for easy detection and cure of different infectious diseases. The chapter also puts forward a deeper understanding of the principle underlying tunable fluorescent properties, and the recent efforts for developing efficient fluorescent photosensitizers. 2022 Nova Science Publishers, Inc. -
Food Quality Indicator-Based Intelligent Food Packaging
Foodborne illnesses caused by microbial growth and consumption of spoiled food items can lead to severe health issues. Monitoring real-time food quality through indicators/sensors has been an important priority for food industries, researchers, consumers, and regulatory bodies in this context. Intelligent packaging (IP), a type of food packaging, uses an indicator component to track and alert consumers on the quality of packaged food from the stage of manufacture to consumption in real time. Intelligent packaging helps reduce food waste and ensure consumer safety. This book chapter will discuss various food quality indicators, including humidity, oxygen, carbon dioxide, pH, and microbial indicators, and their applications in IP. 2025 John Wiley & Sons Ltd. All rights reserved. -
Food Security and Global Institutions: A Global Justice Perspective
Food security refers to a condition where all people have physical and economic access, at all times, to sufficient, safe and nutritious food that meets their needs and food preferences to lead an active and healthy life. Universal Declaration of Human Rights, 1948 (UDHR) declares the right to food as a basic human rights. International Covenant on Economic, Social and Cultural Rights, 1976 (ICESR) explicitly recognises the right of everyone to food and mandates all state parties for its realization; also it recognizes everyones right to be free from hunger as a fundamental right. Further, it instructs the state parties to ensure equitable distribution of world food supplies to achieve the right of everyone to be free from hunger. Rome Declaration on World Food Security, 1996 reaffirmed the right of everyone to access to safe and nutritious food compatible with right to adequate food and also right to be free from hunger. United Nations Millennium Declaration set the goal for fighting hunger and resolved to reduce the proportion of people suffering from hunger to half by 2015, then Sustainable Development Goals were floated, inter alia, to end extreme poverty and achieve the target of zero hunger and food security by 2030. Regardless of its being a universal human rights, food security scenario across the globe is far from satisfactory and fair. Post COVID 19 scenario has seen a surge in undernourishment and food insecurity. According to The State of Food Security and Nutrition in the World, 2022, 3.1 billion people across the globe are unable to afford a healthy diet. At this juncture we are living in a deeply connected and globalized world run not by national institutions but by global institutions. The role of global institutions assume significance in a globalized world. Justice demands that policy planning and legal framework on food security should be fair and equitable; they should be based on the idea of entitlement and obligation. To achieve the goal of zero hunger and food security, what is required is an equitable and unified global governance approach premised upon the idea of global justice which shall fix obligations on global institutions. This chapter aims at examining the issue of food security from a global justice perspective and how it can be sustainably achieved. It will explain the concept of global justice and obligations of global institutions by relying upon few legal and political theories. Further, the chapter will explain the human rights perspective of the food security and the challenges involved with it. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.