This book provides broad coverage of data science and ML fundamentals to materials science researchers so that they can confidently leverage these techniques in their research projects.
This book provides broad coverage of data science and ML fundamentals to materials science researchers so that they can confidently leverage these techniques in their research projects.
Parvathi Chundi, PhD is Professor of Computer Science, University of Nebraska-Omaha. Prior to Omaha, Dr. Chundi was with Agilent Technologies and HP Labs, both in Palo Alto, CA. Venkataramana Gadhamshetty, PhD, PE is Professor of Environmental Engineering in Department of Civil and Environmental Engineering, South Dakota School of Mines and Technology. He is a cofounder of 2D materials for Biofilm Science Engineering and Technology (2DBEST) center and 2D materials laboratory (2DML) at SDSM&T. Bharat K. Jasthi, PhD is Associate Professor, Department of Materials and Metallurgical Engineering, South Dakota School of Mines and Technology. Dr. Jasthi has research expertise in the areas of microstructural modification, structure property correlation, new alloy development, powder metallurgy, additive manufacturing, and development of engineered surface thin films and coatings for a wide range of applications. Carol Lushbough, MA is an Emeritus Professor of Computer Science, University of South Dakota.
Inhaltsangabe
Chapter 1 Introduction to Machine Learning for Analyzing Material-Microbe Interactions Venkataramana Gadhamshetty Parvathi Chundi and Bharat K. Jasthi Chapter 2 Introduction to 2D Materials Roberta Amendola and Amit Acharjee Chapter 3 An Overview of Machine Learning Dilanga Abeyrathna Mahadevan Subramaniam and Parvathi Chundi Chapter 4 Discovery of 2D Materials with Machine Learning Md Mahmudul Hasan Rabbi Sikder Bharat K. Jasthi Etienne Z. Gnimpieba and Venkataramana Gadhamshetty Chapter 5 Bacterial Image Segmentation through Deep Learning Approach Ejan Shakya and Pei-Chi Huang Chapter 6 Self-Supervised Learning-Based Classification of Scanning Electron Microscope Images of Biofilms Md Ashaduzzaman and Mahadevan Subramaniam Chapter 7 Quorum Sensing Mechanisms Biofilm Growth and Microbial Corrosion Effects of Bacterial Species Vaibhav Handa Saurabh Dhiman Kalimuthu Jawaharraj Vincent Peta Alain Bomgni Etienne Z. Gnimpieba and Venkataramana Gadhamshetty Chapter 8 Data-Driven 2D Material Discovery Using Biofilm Data and Information Discovery System (Biofilm-DIDS) Tuyen Do Alain Bomgni Shiva Aryal Venkataramana Gadhamshetty Diing D. M. Agany Tim Hartman Bichar D. Shrestha Gurung Carol M. Lushbough and Etienne Z. Gnimpieba
Chapter 1 Introduction to Machine Learning for Analyzing Material-Microbe Interactions Venkataramana Gadhamshetty Parvathi Chundi and Bharat K. Jasthi Chapter 2 Introduction to 2D Materials Roberta Amendola and Amit Acharjee Chapter 3 An Overview of Machine Learning Dilanga Abeyrathna Mahadevan Subramaniam and Parvathi Chundi Chapter 4 Discovery of 2D Materials with Machine Learning Md Mahmudul Hasan Rabbi Sikder Bharat K. Jasthi Etienne Z. Gnimpieba and Venkataramana Gadhamshetty Chapter 5 Bacterial Image Segmentation through Deep Learning Approach Ejan Shakya and Pei-Chi Huang Chapter 6 Self-Supervised Learning-Based Classification of Scanning Electron Microscope Images of Biofilms Md Ashaduzzaman and Mahadevan Subramaniam Chapter 7 Quorum Sensing Mechanisms Biofilm Growth and Microbial Corrosion Effects of Bacterial Species Vaibhav Handa Saurabh Dhiman Kalimuthu Jawaharraj Vincent Peta Alain Bomgni Etienne Z. Gnimpieba and Venkataramana Gadhamshetty Chapter 8 Data-Driven 2D Material Discovery Using Biofilm Data and Information Discovery System (Biofilm-DIDS) Tuyen Do Alain Bomgni Shiva Aryal Venkataramana Gadhamshetty Diing D. M. Agany Tim Hartman Bichar D. Shrestha Gurung Carol M. Lushbough and Etienne Z. Gnimpieba
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