Singh Punit Kumar (58 results)

Hardcover. Condition: New. 1st Edition. Contents: 1. Value creation through social entrepreneurship: a collection of five caselets/Siddhartha Saxena. 2. Corporate social responsibility and social entrepreneurship: emerging growth and employment opportunities/Mitali Tiwari. 3. Corporate Governance in the changing scenario/Atul Bansal. 4. The growing contribution of social entrepreneurship: a case study on innovation mobile school/Anuradha R. Tiwary and Shefali Bajaj. 5. Corporate social responsibility: need for survival/Anupam Sharma. 6. Innovative strategy by social enterprise: a case of SRVSEWA (B)/Mayank Saxena and Pushyamitra Joshi. 7. Skeptically forestalling fraudulent financial reporting in public listed manufacturing companies in Nigeria: the role of the Beneish Model/Emma I. Okoye, Ugochukwu J. Nwoye and Chikwelu M. Mbonu. 8. Women entreprenurship and corporate social responsibility: a case study of active pharmaceuticals/Ankita Sajjan. 9. Social entreprenurship-a tool for empowerment/Harnam Singh. 10. Analysis of Rural entrepreneurship under the theoretical approach of resource and capabilities: the case of a rural microbusiness in Mexico/Jose G. Vargas Hernandez. 11. Kachchi Kali: a step towards big cause/Ajit Upadhyaya, Punit K. Dwivedi, Suyash Jhawar and Rajeev Shukla. 12. Agri credit and rural indebtedness in Haryana: an Imperial study/Ajit Singh. 13. Agripreneurship: a way for rural development through experimental approach/Kishor H. Gedam and Rachna K. Gedam. 14. Overview of female workers in rural Uttar Pradesh: an inter-district analysis/Kavita Baliyan. 15. Environmental initiatives in Cummins: making people's lives better/Ashima Joshi, Amit Chauhan and Amitabh Joshi. 16. Women entrepreneurs: success stories/Nivedita T. Dwivedi. 17. Women entrepreneurship in India/Anoop Kumar Singh and Sabahat Shamim. 18. Energy efficient data centers for the success of cloud computing paradigm/Manju Lata. 19. Role of information technology in rural planning and development: a case study of Lucknow district/Ritu Jain. 20. Case study on corporate social responsibility/Karanam Nagaraja Rao and Aswathi Nair. 21. A detail study on HR disclosure in corporate social responsibility reporting of selected companies in India/Vasudev Modi. 22. Where lies the key?/Rajeev Shukla, Ajit Upadhyaya and Punit Kumar Dwivedi. 23. New horizon of the commercial banking in Indian prospective/Tahira Akhtar. 24. Impact of corporate Governance on corporate finance-an Indian perspective/Anshu Dixit and Ankita Sajjan. SAVERA has been serving society as an academic forum to provide critical inputs on major issues, relevant to development of rural India and to seek appropriate representation on the various committees, bodies, delegations, conferences, seminars, books, journals etc. at the state, National and International levels in association with professionals, research-scientists, social-scientists, reformists, technocrats, and agriculturists. It also promotes, facilitates, research activities to contribute academia and government for policy formation and guides the rural artisans and people in obtaining knowledge about rural enterprise development. It organizes integrated programmes for inclusive development of marginalized part of the society and economic development of rural India. It has been trying to develop indigenous literature for rural entrepreneurship development with various research initiatives and supporting quality researches. SAVERA also guides and encourages villagers to establish cottage, micro and small business units in rural areas. Corporate social Responsibility and social entrepreneurship is an attempt to further the vision of SAVERA in the field of entrepreneurship teaching collectively, the book puts forward the idea of teaching cases in CSR and social entrepreneurship for classroom discussion. Therefore, it becomes obligatory to produce a complete literature of cases in entrepreneurship. The present edition is a collection of scholarly written teaching cases on the.…

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Hardcover. Condition: New. Contents: 1. Mulching: A Sustainable Approach in Vegetable Production. 2. Self-sufficiency and Agriculture Trade: India's Prospects and Challenges Under New Global Framework. 3. Artificial Intelligence (AI): A New Paradigm for Sustainable Environment & Agriculture. 4. Knowledge of Rice and Wheat Farmers About Various Aspects of Agrochemical Use and Plant Protection Practices in the Sub-tropics of Jammu. 5. Extend of Adoption vis-a-vis Technological Gaps in Adoption of Recommended Practices of Maize Cultivation in District Ganderbal. 6. Climate Smart Agriculture for Food Security. 7. Marketing Management: An Overview. 8. Overview of Climate Change in India with Special Reference to J&K. 9. Weather Forecast Based Agro Advisory Services under Climate Change Scenario. 10. Organic Agriculture: Helps Mitigate Climate Change. 11. Climate Smart Agriculture: A Promising Approach Towards Sustainable Farming. 12. Novel Advances in Sensing and Remediation of Noxious Pollutants. 13. Decadal Dynamics of Urban Blue Infrastructure with Special Reference to Dal Lake of Srinagar City. 14. Indigenous Technical Knowledge: Relevance in the Present Day Agriculture. 15. Carbon Sequestration Potential of Agroforestry Systems: An Overview. 16. Climate Change and Livestock Production. 17. Pillars of Climate Smart Agriculture. 18. Application of 4.0 for Sustainable Aquaculture and Nutritional Security. 19. Climate Smart Agriculture and Food Security in India. 20. Biotechnological Advances in Mulberry Crop Improvement. 21. Climate Change and Its Impact on Poultry Production. 22. Climate Smart Agriculture. 23. A Comprehensive Approach to Combat Climate Change: Integrating Mitigation and Adaptation Strategies. 24. Natural Farming: An Opportunity for Sustainable Agriculture. The concept of Climate Smart Agriculture (CSA) was launched by FAO in 2009 which goes beyond agricultural practices and technologies to include enabling policies and institutions as well as identification of financing mechanisms to accomplish sustainable agricultural development through the integrated approach of managing landscapes to help adapt agricultural methods, livestock and crops in context of changing climatic scenarios. It has gained considerable attention, especially in developing countries, due to its potential to increase food security and farming system resilience while decreasing greenhouse gas emissions, as well as the selection of technology that will best encourage sustainable agricultural practices. Global agriculture has improved over several years, which highlight how we move forward in terms of increased crop production. Agriculture 4.0 is a term for the next big trends facing the industry, including a greater focus on precision agriculture, the internet of things (IoT), artificial intelligence, robotics and the use of big data to drive greater business efficiencies and enhance productivity in the face of rising populations and climate change. …

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Condition: New. 1st edition NO-PA16APR2015-KAP.

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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

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Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.

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Paperback. Condition: New. Biomedical engineering is undergoing a transformation because of AI, which is allowing creative solutions that enhance patient outcomes, diagnosis, treatment planning, and healthcare delivery. Artificial Intelligence and Cloud Computing Applications in Biomedical Engineering examines the salient characteristics of AI in biomedical engineering, highlighting its practical applications and new directions. Highlights of the book include:Genome sequence and visualizationThe role of AI and cloud in detection of diseasesNature-inspired algorithms for disease detectionFrameworks for disease classificationWith a focus on designing AI techniques for disease detection, the book explores the role of AI in biomedical engineering. It discusses how machine learning (ML) and deep learning (DL) are at the heart of AI applications in biomedical engineering. ML algorithms, particularly those based on neural networks, enable computers to learn from large datasets, identify patterns, and make predictions or decisions without explicit programming, and implementing ML algorithms is a focus of the book. Another focus is on DL, a subset of ML, and how it uses multi-layered neural networks to achieve high accuracy in such complex tasks as image and speech recognition. Biomedical engineering generates massive amounts of data from medical imaging, genomic sequencing, wearable devices, electronic health records (EHR), and other sources. This book also discusses AI-driven big data analytics, which allows researchers and clinicians to derive from data meaningful insights, aiding in early disease detection, personalized treatment plans, and patient monitoring.…

Paperback. Condition: Brand New. 264 pages. 9.18x6.12x9.21 inches. In Stock.

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Paperback. Condition: New. Biomedical engineering is undergoing a transformation because of AI, which is allowing creative solutions that enhance patient outcomes, diagnosis, treatment planning, and healthcare delivery. Artificial Intelligence and Cloud Computing Applications in Biomedical Engineering examines the salient characteristics of AI in biomedical engineering, highlighting its practical applications and new directions. Highlights of the book include:Genome sequence and visualizationThe role of AI and cloud in detection of diseasesNature-inspired algorithms for disease detectionFrameworks for disease classificationWith a focus on designing AI techniques for disease detection, the book explores the role of AI in biomedical engineering. It discusses how machine learning (ML) and deep learning (DL) are at the heart of AI applications in biomedical engineering. ML algorithms, particularly those based on neural networks, enable computers to learn from large datasets, identify patterns, and make predictions or decisions without explicit programming, and implementing ML algorithms is a focus of the book. Another focus is on DL, a subset of ML, and how it uses multi-layered neural networks to achieve high accuracy in such complex tasks as image and speech recognition. Biomedical engineering generates massive amounts of data from medical imaging, genomic sequencing, wearable devices, electronic health records (EHR), and other sources. This book also discusses AI-driven big data analytics, which allows researchers and clinicians to derive from data meaningful insights, aiding in early disease detection, personalized treatment plans, and patient monitoring.…

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