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                <text>Lower level of income, underdeveloped industrial bases, lower standards of living and a lack of access to modern technology are the basic challenges of any developing economy. Expansion of the small business sector plays a pivotal role in growing the economies of developing countries and reducing unemployment. Digital marketing is an online platform to promote small- and medium-sized enterprises (SMEs) to reach a global audience without a physical presence in multiple locations. This is particularly beneficial for SMEs in developing countries, where access to international markets may otherwise be limited. The present chapter is a review of global digital marketing strategies and explores how developing nations, particularly India and Southeast Asian countries, can benefit from them and can adopt the advanced strategies to establish the SME sector. It is found that while digital marketing offers substantial benefits for SMEs in India and Southeast Asia, its adoption is influenced by a range of factors, including digital infrastructure, government support and access to digital literacy programs. SMEs in India and Southeast Asia should overcome the existing barriers and continuously adapt to the evolving digital landscape to realize the potential of digital marketing.  2026 Sabita Bhagabati</text>
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                <text>Anubha, Department of Tourism and Hospitality Management, Jamia Millia Islamia (a Central University), New Delhi, India; Hussain S., Department of Tourism and Hospitality Management, Jamia Millia Islamia, India; Mohanty P., Department of Business Administration, Christ University, Bengaluru, India; Gavinolla M.R., National Institute of Tourism and Hospitality Management, Hyderabad, India</text>
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                <text>This chapter examines how digital transformation can address mental health inequities among informal workers in India, focusing on discrimination, labor precarity, and unequal access to care. Using empirical insights from Kerala within broader national and global contexts, it analyzes how psychological distress among native and migrant workers emerges from intersecting socioeconomic, institutional, and digital factors. Drawing on psychology, public health, economics, and digital governance, the chapter proposes a phygital mental health framework integrating physical services with digitally enabled care pathways. Emphasis is placed on ethical leadership, data governance, and economic sustainability, highlighting both opportunities and risks of digital mental health expansion. The chapter demonstrates how compassionate, inclusive, and accountable digital reforms can translate mental health policy into effective instruments for equity, social justice, and sustainable health system transformation.  2026 by IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>P. Karthik P.K., St. Francis Evening College, Christ University, India; SriSai V., School of Business and Management, Christ University, India; Parmar D.V., Parul University, India; Trivedi N.B., Parul University, India; Aggarwal V., Chandigarh University, Mohali, India; D. Ramya D.R., Department of English, Kongu Engineering College, Erode, India; M. Suresh M.S., KPR Institute of Technology, Kovai, India</text>
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                <text>Sandhya H., Christ University, Bangalore, India; Varghese B., Christ University, Bangalore, India</text>
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                <text>Over the past decade, Indias travel and tourism sector has experienced consistent growth in terms of the volume of inbound, outbound, and domestic travelers. The COVID-19 pandemic in 2020 precipitated an economic downturn in the worldwide tourism industry. The tourism and hospitality industry encountered an unparalleled and unfavorable situation as a result of the governments implementation of travel restrictions and stringent quarantine regulations. Both leisure and business travelers were forced to cancel or delay their travel plans, which led to significant penalties for making last-minute changes to their reservations. Destinations around the globe have implemented unique strategies and elements to enhance their resilience in the aftermath of the pandemic. While a significant number of travel agents and tour operators incurred substantial financial losses, a select few recognized this situation as an opportunity and introduced a range of inventive products, along with implementing innovative marketing and promotion strategies. Quarantine stays, Untact Tourism, and Virtual Tourism are neologisms that have gained popularity in the aftermath of the pandemic. Travel businesses have integrated technology and proved to be digitally adaptive business entities. The objective of this study is to comprehend and assess the technology-embedded recovery strategies implemented by the tourism industry in the state of Kerala, located in South India, following the pandemic. The study conducted comprehensive interviews with distinguished travel and hospitality experts from the state. The collected data were utilized to analyze the repercussions of the pandemic on the travel industry in the state, as well as to evaluate the efficacy of the measures implemented by businesses after the pandemic in terms of generating revenue and rebuilding the reputation of the destination. An in-depth examination of the tourism and hospitality websites has proven valuable in comprehending the marketing tactics employed by the companies amidst the COVID-19 pandemic. The studys findings can aid stakeholders in the tourism industry in devising effective measures to endure a pandemic by implementing innovative and creative product development and crisis management strategies.  2026 World Scientific Publishing Europe Ltd. All rights reserved.</text>
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                <text>Artificial Intelligence; COVID-19; Digital revolution; Smart applications; Tour operations; Travel agency; Virtual tourism</text>
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                <text>Digital Soil Texture Classification Using Machine Learning Approaches</text>
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                <text>Feature extraction; Image processing; Neural network; Soil texture classification; Support vector machines</text>
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                <text>The texture of the soil is an important factor to consider during cultivation. The water transmission property is being regulated by the texture of the soil. To determine sand, silt and clays percentage present in a soil sample, a conventional laboratory method is used, which consumes more time. Digitization in agriculture has given a new direction of innovative research in agriculture domain. In this paper, based on image processing an efficient model has been developed for soil texture classification. Eight different image preprocessing techniques were used for the image enhancement. Out of that, the linear contrast adjustment found to be best in image enhancement. A feature vector was calculated by extracting six different features from the enhanced image. The feature vector of an image is input to the machine learning classifier. The various classifiers used in this research work are SVM, KNN, ANN and PNN. The accuracy of the classifiers was SVM (0.98), KNN (0.89), ANN (0.89) and PNN (0.86). From the result, it is found SVM model has higher rate in classification of soil.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.</text>
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                <text>Sharmila G.; Rajamohan K.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-1, pp. 133-144.</text>
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                <text>ISSN: 23673370; ISBN: 978-981995014-0</text>
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                <text>Sharmila G., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Rajamohan K., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India</text>
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                <text>Tibrewal, Sanket; Awasthi, Yashmita; Singh, Shanu</text>
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                <text>Digital sustainability models integrating AI for enhanced business and environmental performance</text>
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                <text>Transforming Business Through Digital Sustainability Models;pp.59-80</text>
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                <text>&lt;a href="https://doi.org/10.4018/979-8-3373-0608-7.ch004" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.4018/979-8-3373-0608-7.ch004&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105008859249?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105008859249?origin=resultslist&lt;/a&gt;</text>
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                <text>Tibrewal S., Christ University, Bengaluru, India; Awasthi Y., Christ University, Bengaluru, India; Singh S., Christ University, Bengaluru, India</text>
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                <text>In digital sustainability, it explores AI's transformative role with economic growth coming hand in hand with stewardship of the environment. Industry-specific case studies have been covered within energy, manufacturing, and logistics, covering issues of resource optimization, emission reductions, and circular economy practices-all factored into here. Covered are challenges along data privacy lines, AI bias, and ethics trade-offs plus scalable frameworks, public-private partnerships, and policy recommendations. Potential AI support for SDGs helps envision the potential of such systems in helping sustain resilient, sustainable businesses. Introducing AI helps organizations innovate toward environmental responsibility and work toward a sustainable future by global collective efforts.  2025 by IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>Digital Technologies in Modeling and Management: Insights in Education and Industry explores the use of digital technologies in the modeling and control of complex systems in various fields, such as social networks, education, technical systems, and their protection and security. The book consists of two parts, with the first part focusing on modeling complex systems using digital technologies, while the second part deals with the digitalization of economic processes and their management. The book results from research conducted by leading universities' teaching staff and contains the results of many years of scientific experiments and theoretical conclusions. The book is for a wide range of readers, including the teaching staff of higher educational institutions, graduate students, students in computer science and modeling, and management technologies, including economics. It is also a valuable resource for IT professionals and business analysts interested in using digital technologies to model and control complex systems.  2024 by IGI Global. All rights reserved.</text>
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                <text>Prakasha G.S.; Lapina M.; Balakrishnan D.; Sajid M.</text>
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                <text>Digital Technologies in Modeling and Management: Insights in Education and Industry, pp. 1-427.</text>
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                <text>The cyber digital world is an essential variant in day-to-day life in advanced technology. There is a better change in the lifestyle as intelligent technology. In larger excite to increase the advanced technology which can be developed to humans in major dependent on network and internet users. Now, in modern times, the internet has changed the primary need in human lifestyle by giving access to everything in the world while sitting in one place knowing and updating the information and usage of online subscribers or Revolution. The world is moving in Rapid and Faster communications within a fraction of a second, at a lesser cost, and it has minimal paper-based processes and relies on the digitization document instead of a paperless environment. The data is handled by finch security practices, which are used in security worldwide to establish protected data management systems like digital lending, credits, mobile Banking, and mobile payment. Cryptocurrency and blockchain, B-trading, and banking as a service are included. At the same time, leveraging the new technologies is to resist hacking cyber-attacks. This article is also involved in artificial intelligence and machine learning (AI&amp;amp;ML) in different cyber-attacks. This article focuses on genetic algorithms to detect the cyber-attack. The main aim of the detection is future to prevent these cyber-attacks. The comparison will take two sample genetic algorithms. The first one is taken for Ant Colony Optimization (ACO), and the proposed model is taken for Particle Swarm Optimization. The average attack detection of ACO algorithm is 45 packets at the same time PSO algorithm will detect 50 packets.   2023 IEEE.</text>
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                <text>Digital transactional tools and their optimum use in language learning: An interdisciplinary approach /</text>
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                <text>IOSR Journal of Humanities and Social Science, Vol.19, Issue 11, pp.230-233, ISSN No: 2279-0845.</text>
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