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Aging Bodies and Necropower: A Critical Study of Geronticide in Tamil Films K.D. and Thalaikoothal
This paper analyzes the act of thalaikoothal, performed on ill and infirm older people in the southern part of the state of Tamil Nadu, India, with reference to two Tamil films, K.D. (2019) and Thalaikoothal (2023), which portray the horrors of the practice. A kind of involuntary euthanasia, the ritual continues to have covert social acceptance as exemplified in the films, favoring the common stereotype that marks aging bodies as unproductive and unworthy of living. Therefore, this article explores the aging bodies in the films as sites of power, controlled by death enforced through Thalaikoothal, employing Mbembes concept of necropower. It also examines the effects of the practice on the elderly, who are compelled to prepare themselves for a forced death. The study further identifies the underlying factors contributing to the prolonged existence of Thalaikoothal even in the present times. 2023, University of Zadar. All rights reserved. -
Aging, sexual intimacy, and challenges in contemporary India: A qualitative study
An individual's life is shaped by age norms practiced in a particular society. In most societies, there is a deadline for every life event. Sexual intimacy is an essential part of every individual. However, sexual intimacy seems appropriate for young individuals, and middle-aged and older are considered asexual. Those who share sexual intimacy at a later age have to face the consequences for this age-inappropriate behavior in society. This study analyses Badhaai Ho film to explore the consequences of sharing sexual intimacy by middle-aged heterosexual couples in their 50s as it is forbidden by prevalent social norms. This study also explores the role of family in dealing with the repercussions of actions against the prescribed social norms. Thematic analysis suggests that society has a predefined age-bound box for individuals with different age categories. The middle-aged couple suffers various consequences for breaking the prescribed age-bound box. The role of the family is found to be crucial in mending the box by replacing it with an updated version. There are also gender differences in attitude toward sexual intimacy. Implications of this study can be utilized to explore the pathway of social change in existing social (age) norms in any society. Copyright 2022 Srivastava and Upadhaya. -
AGNI II
AGNI II, a commemorative postage stamp on the Defence Research and Development Organisation (DRDO) of India was issued on 1 January, 2000. Through the issue of the stamp, commemorating, the successful flight testing of intermediate range ballistic missile - AGNI II, emphasizing the the country's defence programmes " peaceful deterrence" -
AGRI 4.0 AND THE FUTURE OF CYBER-PHYSICAL AGRICULTURAL SYSTEMS
Agri 4.0 and the Future of Cyber-Physical Agricultural Systems is the first book to explore the potential use of technology in agriculture with a focus on technologies that enable the reader to better comprehend the full range of CPS opportunities. From planning to distribution, CPS technologies are available to impact agricultural output, delivery, and consumption. Specific sections explore ways to implement CPS effectively and appropriately and cover digitalization of agriculture, digital computers to assist the processes of agriculture with digitized data and allied technologies, including AI, Computer Vision, Big data, Block chain, and IoT. Other sections cover Agri 4.0 and how it can digitalize, estimate, plan, predict, and produce the optimum agricultural inputs and outputs required for commercial purposes. The global team of authors also presents important insights into promising areas of precision agriculture, autonomous systems, smart farming environment, smart production monitoring, pest detection and recovery, sustainable industrial practices, and government policies in Agri 4.0. 2024 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
Agricultural credit and agricultural productivity across Indian states: An analysis
The study analyses the relationship between formal agricultural credit and agricultural productivity in India. Secondary data have been collected from various sources for the selected states of Andhra Pradesh, Assam, Bihar, Gujarat, Haryana, Himachal Pradesh, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Punjab, Rajasthan, Odisha, Tamil Nadu, Uttar Pradesh and West Bengal for the time period 19901991 to 20172018. Fixed effect model is used to perform the state-level panel data analysis to establish the relationship between the agricultural credit and agricultural productivity. In addition to this, the study also focuses on analysing the effectiveness of Doubling of agricultural credit policy. The findings from the analysis show that direct agricultural credit and doubling of agricultural credit policy has a positive impact on productivity, whereas the indirect credit has a significant negative impact on productivity. In order to increase agricultural productivity, policies should focus on providing direct credit at a larger scale. 2021 John Wiley & Sons, Ltd. -
Agricultural Crop-Yield Prediction: Comparative Analysis Using Machine Learning Models
Machine learning (ML) is a crucial decision-support tool for predicting agricultural crop yields, enabling choices about which crops to grow and what to do while they are in the growing season. The research on agricultural production prediction has been supported by the application of several ML techniques. We employed a comparative analysis in this study to synthesize using three ML models, including linear regression, polynomial regression, and K-nearest neighbors (KNN), and extracted the results for the prediction of yield. Crop yield depends on a variety of aspects such as temperature, pesticide usage, rainfall, and even year due to changing climatic conditions. It is in our best interest to find out the crop yield based on these factors, as it will help in advancing the farming sector. These collected data have gone through preprocessing - i.e., cleaning, to ensure that no redundant or error data is used to train the ML models. Before we train the models, the dataset is divided into training and testing to provide the performance metrics of each model we use. The experimental results on predictions indicate KNN performs slightly better in comparison with linear regression and polynomial regression models. 2024 Taylor & Francis Group, LLC. -
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Agricultural Internet of Things (AIoT) Architecture, Applications, and Challenges
The internet of things (IoT) is a system that involves adding sensors, software, and network connectivity to physical devices, enabling them to collect and exchange data. This technology has the potential to bring significant advancements to various sectors, including agriculture. In farming, the agricultural internet of things (AIoT) utilizes IoT to improve efficiency, sustainability, and productivity. Through the real-time collection and analysis of data, AIoT can optimize growing conditions, prevent diseases and pests, and ultimately increase crop yields. By monitoring factors such as soil moisture, temperature, and nutrient levels, AIoT technology can effectively track crop health and detect potential issues in advance. In this way, AIoT technology is helping farmers to make more informed decisions and take more effective actions to improve crop yields, reduce waste, and lower costs. AIoT in agriculture finds practical applications in smart irrigation systems, precision agriculture, livestock monitoring systems, and climate control systems. Smart irrigation systems utilize weather data and soil moisture sensors to efficiently manage water consumption. Precision agriculture employs sensors and data analysis techniques to optimize planting, fertilization, and pest control practices. Livestock monitoring systems aid in monitoring and managing the well-being of farm animals. Climate control systems utilize AIoT to regulate and optimize environmental conditions for crops and livestock. Livestock monitoring systems use sensors to track the health and well-being of animals. Climate control systems for greenhouses and barns use AIoT devices to monitor temperature, humidity, and other environmental factors to optimize growing conditions. Sensors can be used to monitor various environmental factors in a farm, by connecting the sensors to a cloud-based platform for storing and analyzing data. The wireless sensor networks can be used to calculate the dew point on leaves and adjust the greenhouse environment to prevent and control plant diseases. Drones equipped with sensors, cameras, and other imaging technology can also be used to monitor crop conditions, as this allows farmers to take proactive measures to address these issues, preventing crop loss and reducing the need for pesticides and other chemicals. IoT/sensor nodes are vital components in precision agriculture as they gather real-time data. Integrating data analytics and machine learning into the agricultural system improves its practicality and efficiency. Real-time data availability enhances precision in agriculture, and combining data analytics with this information leads to notable progress in the field. However, AIoT technology is gradually advancing in agriculture, but there is a need for a more rigorous research approach in this area. Additionally, the current literature lacks coherence and solid research on the interconnectedness of technology and agriculture. 2024 selection and editorial matter, Alex Khang, Vugar Abdullayev, Vladimir Hahanov and Vrushank Shah; individual chapters, the contributors. -
Agricultural nanotechnologies: Future perspectives of bio-inspired materials
Bio-inspired designs have been used by humankind in understanding and modelling novel materials which have applications in diverse fields like disease diagnostics, drug delivery, agriculture, energy storage, industry, etc. Superhydrophobicity, directional adhesion, structural colour, self-cleaning, antireflection, etc. are some of the useful attributes for which we have relied a lot on nano level biomimetics. Bioinspired nanolevel designs have been explored in the field of agriculture too. Such nanomaterials and nanodesigns have been used to increase crop yields. They also find uses in fertilizer application and replacement of many harmful chemical pesticides, which are generally overused. Increasing population, increased longevity of people and the urgent need for sustainable environment have led to a dire need for exploration and adaptation of such novel technologies which can help in feeding the growing population. Nanoscale products and technologies can also help in reducing the accumulation of excess fertilizers, pesticides, etc. in soil, which can go a long way in cleaning up the environment. The current attempt is intended to portray the latest developments and future possibilities of bioinspired NT in diverse fields of agriculture like synthesis and delivery of novel pesticides and fertilizers, nanocarriers for gene delivery, sensors to monitor and assess soil conditions, plant pathogen detection and plant nanobionics to detect pollutants. 2023 Bentham Science Publishers. All rights reserved. -
Agricultural waste valorisation Novel Areca catechu L. residue blended with PVA-Chitosan for removal of chromium (VI) from water Characterization, kinetics, and isotherm studies
Arecanut, an industrial crop prevalent in tropical regions such as India, Sri Lanka, and parts of Southeast Asia, generates significant agricultural waste during processing. This study explores a waste-to-wealth approach by incorporating arecanut organic residue into Polyvinyl alcohol (PVA) - Chitosan blends via an eco-friendly continuous stirring method to develop an adsorbent film for removing chromium (VI) from water. Morphological analyses confirmed enhanced surface area, porosity, and roughness in the blended films. XRD and FTIR analyses indicated a semi-crystalline nature with a decrease in the characteristic peak intensity of PVA and chitosan, confirming the incorporation of arecanut residue. Optimal conditions identified OR-4 film, using 0.4 g of adsorbent, achieving 88.68 % removal of 173 mg/L chromium (VI) at pH 9.0, within 45 minutes at 40C. SEM images demonstrated significant surface roughness reduction before and after adsorption, confirming chromium adsorption. Kinetic studies revealed a pseudo-second-order model and adsorption isotherms confirmed film surface heterogeneity. This research advances eco-friendly materials for water purification and offers a sustainable solution for managing agricultural residues. 2024 Elsevier B.V. -
Agriculture 4.0 and smart farming: Imperatives of scaling up innovation and farmer capabilities for sustainable business
Smart agriculture adoption during industry 4.0 is creating new scenarios to farmers across the world. Smart farming promotes not only an increase in the agricultural productivity and incomes, but also building resilience to climate change. Small business farmers had to look at all possible means to cope with the technology applications for implementation of agro-transformation agendas for improved production and business performance. Smart farmers have to make use of several technology applications like drones and satellites, IoT (Internet of Things) based sensors, block chain and big data, biotech, farm maintenance technology (optimising water usage, production, and innovation technology) for better agricultural practices. Though such aggrotech opportunities have demonstrated business improvements, how far such smart farming revolution is well received by the agribusiness owners are less researched into. Henceforth, the purpose of this research is to establish the relationship between aggrotech innovation capabilities and farmer's capabilities associated with agriculture firms and its contributions to business performance. Following cross-sectional descriptive study design, and purposive sampling, the study addressed 3 direct and 2 indirect relationships in the model, on 212 farmers. The data was collected from Selangor state of Malaysia. The study applied Smart PLS SEM to analyse the data. The results show that the innovation (technology) capability and farmer's (people) capability have a positive relationship on business performance. The study also shows the partial mediation effect of technology change on innovation capability and business performance as well as employee capability and business performance. The study is novel in its form by applying Resource Based View theory on Smart agriculture, extending possibilities of generalization agriculture sector. 2021 Ecological Society of India. All rights reserved. -
Agriculture as a means of alleviating rural poverty: Pursuant to the sustainable development goal-1
Poverty is one of the worst problems prevailing in the world. The poorest in the world are often without food, have little or no access to education, basic amenities of life, and lack health facilities. Eradication of Global Poverty eradication is a herculean and complex task. The origination of 2030 Agenda to eradicate poverty was done after the successful completion of the anti-poverty Millennium Development Goal, but still, a vast number of people were living in poverty and a great number among them were living in extreme poverty. So, the 2030 Agenda for Sustainable Development called for the eradication of poverty in all poverty in forms from every corner of the world by almost half. In backward and developing nations, poverty is more rampant in rural areas. The economies of most of these nations are predominantly based on Agriculture and therefore progress in agriculture is viewed as a potent tool to eradicate rural poverty. However, there are serious issues that are required to be addressed in this regard. This chapter explores some vital issues related to agriculture which require the attention of the policymakers, to achieve the objective of reducing rural poverty through advancement in agriculture. 2023 Nova Science Publishers, Inc. All rights reserved. -
Agriculture water purifying device /
Patent Number: 363685-001, Applicant: S Nithyananthi. -
Agro-food traceability with efficient user interface using blockchain technology
Food traceability is crucial for food quality and safety to reduce vulnerabilities of product globalization. The traditional Agri-food production system does not offer easy traceability of the product at any point of the supply chain. Blockchain based production system resolves the challenges by reducing the complexity of traceability. Still no other study has presented Blockchain-based traceability platform with a lower impact on the environment and lower cost for each transaction sent by the supply chain. In the existing system, proof of work consensus protocol is used in blockchain which consumes more energy for transactions. The proposed traceability system is based on Ethereum Blockchain, which uses the Proof-of-Stake mechanism of consensus that requires minimal computational power, is highly scalable and environmentally sustainable. The user interface of consumer is specially designed that provides all the tracking information of the agro-food. The developed traceability platform digitizes the entire production chain making the data immutable and available in realtime. 2024 by IGI Global. -
AI and IoT for universal health and well-being across generations
Over the last several years, the confluence of AI and the Internet of Things (IoT) has caused tremendous changes in many areas of our life, including the healthcare industry. Because of this cooperation, new possibilities have emerged with the aim of enhancing the health and welfare of people across all different generations. The ability to efficiently gather, analyze, and derive insights from large volumes of real-time data has revolutionized healthcare, allowing for better patient treatment and community health management. This is made feasible by combining algorithms powered by artificial intelligence with IoT-connected devices. Examining the gamechanging possibilities of AI and the IoT in the healthcare industry is the goal of this introductory piece. The function of AI and the Internet of Things in advancing health equity and wellness across diverse age groups is the primary emphasis of this study. Countless and varied uses of AI and the internet of things may be found in the medical field. Some examples of these uses include remote patient monitoring and the development of predictive analytics tools for use in illness prevention.Health outcomes and quality of life for individuals of all ages can be improved via the development of individualized therapies and treatment programs that cater to each person's specific needs. It is feasible to create these opportunities with the help of these technologies. Healthcare issues may be effectively addressed in a variety of locations, from densely populated cities to more rural places, by implementing solutions that leverage the internet of things and artificial intelligence. Because these solutions are both accessible and scalable, this is the result. It is possible for healthcare systems to overcome barriers to service delivery and access by utilizing these technologies. As a result, people of all ages and from all over the world will be able to live the kind of healthy, fulfilling lives they deserve. 2024, IGI Global. All rights reserved. -
AI and IoT in Improving Resilience of Smart Energy Infrastructure
In todays world, we cant live without energy. Its essential for the growth and development of the economy. Changes in climate, sustainable growth, health, food security for the world, and environmental protection all require it if we are to make any headway. Governments around the world are looking for innovative ways to generate, control, supply, and save energy because of the rising cost and rising demand for it. Photovoltaic systems, hydropower, wind energy, tidal power, and geothermal energy are examples of traditional renewable energy sources that have advanced significantly in recent years. They, however, are unable to deal with environmental variations. It is critical to developing smart and cost-effective generators in order to meet the advanced worlds energy demands. In this chapter, we introduced the concept of smart energy, smart grid, and smart energy systems in a brief manner. Smart energy portfolio and smart energy management are introduced in the frst section. We also discuss how AI and IoT can be used to improve the different energy sources like wind power, solar power, geothermal power, etc. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
AI and Machine Learning Applications in Predicting Energy Market Prices and Trends
The worldwide energy market is intricate and unstable, shaped by several aspects including geopolitical occurrences, supply-demand variations, and regulatory modifications. Precisely forecasting energy prices and trends is essential for stakeholders, such as energy producers, dealers, and policymakers. This study investigates the utilization of artificial intelligence (AI) and machine learning (ML) to improve energy price forecasting models. Conventional forecasting methods frequently fail to account for the dynamic and non-linear characteristics of energy markets; however, AI/ML techniques, including neural networks, decision trees, and reinforcement learning, provide enhanced prediction precision. By including external variables such as meteorological conditions and economic metrics, AI models can produce more accurate and useful insights. Case studies illustrate the effective implementation of AI in energy markets, showcasing its capacity to surpass traditional methods. This article addresses difficulties such as data quality and computing expenses while delineating potential developments in AI-driven energy market forecasts. The Authors, published by EDP Sciences. -
AI and Machine Learning Enabled Software Defined Networks
The telecommunications industry has not been exempt from the technology sectors massive artificial intelligence (AI) and machine learning (ML) boom in recent years. Artificial intelligence (AI) and machine learning (ML) provide advanced analytics and automation that are in line with modern networking concepts like software-defined networking (SDN) and software-defined wide-area networks (SD-WAN). Work is being done to determine how AI/ML can benefit SD-WAN and to demonstrate these benefits in a real SD-WAN network using a workable example. Modern ML techniques and algorithms are the extent of AI/ML. Todays Internet is under constant threat from DDoS (Distributed Denial of Service) attacks. As the volume of Internet traffic grows, its getting harder and harder to tell whats legitimate and whats malicious. The DDoS attack was detected using a machine learning approach that makes use of a Random Forest classifier. To better detect DDoS attacks, we tweak the Random Forest algorithm. The proposed machine learning approach outperforms, as demonstrated by our results. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
AI and Real-Time Business Intelligence
Timely and accurate knowledge that can be provided to different stakeholders in an enterprise improves the performance and decision-making capabilities with better insight. The information, be it qualitative or quantitative, when made available to decision makers becomes the basis of the business intelligence (BI) that improves functionality, scalability and reliability. The knowledge is managed by application of various data warehousing techniques, and artificial intelligence comes into play by providing an ample number of data mining and machine learning techniques. The chapter aims at analyzing the origin, evolution and development of BI systems and their relationship with artificial intelligence (AI). The chapter also aims to provide new research horizons in the scientific activities and advancements in BI, knowledge management and analysis. 2024 selection and editorial matter, Hemachandran K., Raul V. Rodriguez, Umashankar Subramaniam, and Valentina Emilia Balas; individual chapters, the contributors. -
AI Applications Computer Vision and Natural Language Processing
Artificial intelligence (AI) applications in computer vision and natural language processing (NLP) have made major advances in recent years, challenging a number of sectors and areas. This multidisciplinary topic combines NLP, which examines the study of human language, and computer vision, which concentrates on the understanding of visual data. This study examines the wide range of applications that are included within this convergence, highlighting the revolutionary potential of AI technology. AI has made it possible to make significant advances in autonomous systems, object identification, and image recognition in the field of computer vision. These developments have stimulated innovation and increased efficiency, revolutionizing sectors including healthcare, autonomous vehicles, and security. Meanwhile, AI-driven advances in NLP have produced strong language models that can produce, comprehend, and translate text. These approaches have been utilized to improve accessibility and efficiency of communication in chatbots, sentiment analysis, and language translation services. This chapter explores the basic ideas and advancements in these two fields, emphasizing the opportunities and novel challenges that arise from integrating computer vision and NLP. Additionally covered are data privacy, ethical issues, and the possibility of prejudice in AI applications. The study also highlights the ongoing need for these fields' advancement and investigation in order to solve real-world problems and fully utilize AI's potential in the computer vision and NLP industries. 2025 The Institute of Electrical and Electronics Engineers, Inc.