Yadav pramod kumar (106 risultati)

Soft cover. Condizione: New. Contents: 1. Role of Bioinformatics in Agriculture Sector/Bhavana Tandon, Abhijeet William Singh, Harika Annapragada, Neha Shree Maurya and Satendra Singh. 2. Recent Trends in 'Computational Transcriptomics'/Pramod Katara, Neelam Krishna, Anamika Yadav,Vibha Raj Shanti and Budhayash Gautam. 3. Chemoinformatics: An Overview, Current Status and Future Prospects/Harika Annapragada, Neha Shree Maurya, Bhavana Tandon, Abhijeet William Singh, Ajay Kumar Singh, Pramod Kumar Yadav, Satendra Singh and Dhirendra Kumar. 4. Microarray Data Analysis in Agri-Informatics/Nivedita, Budhayash Gautam, Dhirendra Kumar and Pramod Kumar Yadav. 5. Next Generation Sequencing : An Insilco Approaches for Genomic and Proteomics Data Analysis/Kavita Goswami, Neeti Sanan Mishra, Budhayash Gautam and Vibha Raj Shanti. 6. Database Resources for Medical and Health Science Research/Anil Kumar and Praffulla Kumar Arya. 7. Bioinformatics Approaches in Tomato Genome Studies/Gitanjali Tandon, Neha Shree Maurya, Bhavana Tandon Pramod Kumar Yadav, Satendra Singh and Vibha Raj Shanti. This book broadly highlights about the bioinformatics in agriculture sector, chemoinformatics, database resources for medical and health science researches. This book includes important chapters regarding Microarray data analysis in Agri-Informatics, Next generation sequencing, bioinformatics approaches in tomato genome studies, etc. The coverage of this book will enable reader to update his/her knowledge about bioinformatics concepts as well as applications in different sectors.…

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. pp. 104.

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

Paperback. Condizione: Brand New. 100 pages. 8.66x5.91x0.23 inches. In Stock.

Condizione: New. In English.

Paperback. Condizione: New. The conference aimed to provide a platform for researchers, scientists, technocrats, academicians and engineers to exchange their innovative ideas and new challenges being faced in the field of emerging technologies. It provided an opportunity to exchange ideas among global leaders and experts from academia and industry in developing domains such as machine learning, intelligence systems, smart infrastructure, advanced power technology, and so forth. It covered all broad disciplines of electronics, computer, physical and chemical science engineering.…

Condizione: New.

Taschenbuch. Condizione: Neu. Assessment of Forest Fragmentation and Wildlife Corridor | A Case Study of Kanha-Pench and Nagzira-Navegaon Corridors of Central India | Pramod Kumar Yadav | Taschenbuch | 104 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659504105 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: Brand New. 554 pages. 11.00x8.25x11.00 inches. In Stock.

Condizione: New.

Condizione: New.

Condizione: New. In English.

Condizione: New. In English.

Condizione: As New. Unread book in perfect condition.

Condizione: New. pp. 284.

Condizione: New.

Paperback. Condizione: New. The conference aimed to provide a platform for researchers, scientists, technocrats, academicians and engineers to exchange their innovative ideas and new challenges being faced in the field of emerging technologies. It provided an opportunity to exchange ideas among global leaders and experts from academia and industry in developing domains such as machine learning, intelligence systems, smart infrastructure, advanced power technology, and so forth. It covered all broad disciplines of electronics, computer, physical and chemical science engineering.…

Hardcover. Condizione: new. Hardcover. This book bridges the gap between conventional materials science and emerging data-driven methodologies, highlighting the integration of AI, machine learning, and deep learning technologies to enhance the design, analysis, and optimization of smart materials. It provides a holistic perspective essential for researchers, engineers, and students exploring the intersection of materials engineering and AI technologies.The book examines the connection between recent advancements in materials science and multiscale machine learning, facilitating predictive and prescriptive modeling for assessing material behavior based on composition, structure, and processing. It includes comprehensive discussions on smart material design, optimization, complexity analysis, and advanced computational methods for synthesizing and characterizing materials. Challenges in multiscale modeling, such as biologically inspired material design and the influence of nanotechnology on current trends, are thoroughly explored.Emphasizing the critical role of multiscale machine learning and nanotechnology in creating sustainable smart materials, the book also addresses the ethical implications of this research. It discusses opportunities and challenges in biomaterials, particularly in healthcare and biomedical applications, and anticipates future trends in machine learning for sustainable materials design. The book provides insights into how predictive and prescriptive modeling through machine learning can accelerate the material discovery process, guiding researchers toward promising candidates for further exploration.Serving as a roadmap for researchers and scientists, this book offers valuable insights into innovative approaches that support the future of materials science. mso-bidi-language: AR-SA;">This book bridges the gap between conventional materials science and emerging data-driven methodologies, highlighting the integration of AI, machine learning, and deep learning technologies to enhance the design, analysis, and optimization of smart materials. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

Hardcover. Condizione: Brand New. 300 pages. 9.26x6.11x9.49 inches. In Stock.

Hardcover. Condizione: new. Hardcover. This book bridges the gap between conventional materials science and emerging data-driven methodologies, highlighting the integration of AI, machine learning, and deep learning technologies to enhance the design, analysis, and optimization of smart materials. It provides a holistic perspective essential for researchers, engineers, and students exploring the intersection of materials engineering and AI technologies.The book examines the connection between recent advancements in materials science and multiscale machine learning, facilitating predictive and prescriptive modeling for assessing material behavior based on composition, structure, and processing. It includes comprehensive discussions on smart material design, optimization, complexity analysis, and advanced computational methods for synthesizing and characterizing materials. Challenges in multiscale modeling, such as biologically inspired material design and the influence of nanotechnology on current trends, are thoroughly explored.Emphasizing the critical role of multiscale machine learning and nanotechnology in creating sustainable smart materials, the book also addresses the ethical implications of this research. It discusses opportunities and challenges in biomaterials, particularly in healthcare and biomedical applications, and anticipates future trends in machine learning for sustainable materials design. The book provides insights into how predictive and prescriptive modeling through machine learning can accelerate the material discovery process, guiding researchers toward promising candidates for further exploration.Serving as a roadmap for researchers and scientists, this book offers valuable insights into innovative approaches that support the future of materials science. mso-bidi-language: AR-SA;">This book bridges the gap between conventional materials science and emerging data-driven methodologies, highlighting the integration of AI, machine learning, and deep learning technologies to enhance the design, analysis, and optimization of smart materials. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …

Condizione: As New. Unread book in perfect condition.