Big Data and Visual Analytics

This book provides users with cutting edge methods and technologies in the area of big data and visual analytics, as well as an insight to the big data and data analytics research conducted by world-renowned researchers in this field. The authors present comprehensive educational resources on big data and visual analytics covering state-of-the art techniques on data analytics, data and information visualization, and visual analytics. Each chapter covers specific topics related to big data and data analytics as virtual data machine, security of big data, big data applications, high performance computing cluster, and big data implementation techniques. Every chapter includes a description of an unique contribution to the area of big data and visual analytics. This book is a valuable resource for researchers and professionals working in the area of big data, data analytics, and information visualization. Advanced-level students studying computer science will also find this book helpful as a secondary textbook or reference. Convergence of the life sciences with fields including physical, chemical, mathematical, computational, engineering, and social sciences is a key strategy to tackle complex challenges and achieve new and innovative solutions. However, institutions face a lack of guidance on how to establish effective programs, what challenges they are likely to encounter, and what strategies other organizations have used to address the issues that arise. This advice is needed to harness the excitement generated by the concept of convergence and channel it into the policies, structures, and networks that will enable it to realize its goals. Convergence investigates examples of organizations that have established mechanisms to support convergent research. This report discusses details of current programs, how organizations have chosen to measure success, and what has worked and not worked in varied settings. The report summarizes the lessons learned and provides organizations with strategies to tackle practical needs and implementation challenges in areas such as infrastructure, student education and training, faculty advancement, and inter-institutional partnerships. Contents SUMMARY 1 1 INTRODUCTION 17 1.1 A Science and Technology Revolution is Occurring, 18 1.2 Convergence is an Expanded Form of Interdisciplinary Research, 20 1.3 Convergent Thinking is Advancing Science, 21 1.4 Institutions Need Guidance to Foster Convergence Effectively, 26 1.5 Organization of the Report, 28 2 CONVERGENCE IN ACTION 31 2.1 A Knowledge Network Will Improve Disease Treatment, 31 2.2 Three Dimensional Printing Will Bring New Healthcare Options, 32 2.3 Convergence Occurs in Federal Agencies: ARPA-E, 35 2.4 Convergence Occurs in Industry: Biotechnology, 36 2.5 Convergence Stimulates the Bio-based Economy, 39 3 CONVERGENCE IS INFORMED BY RESEARCH AREAS WITH BROAD SCOPE 43 3.1 Terminology and Concepts, 43 3.2 Many Factors Affect the Success of Integrative and Collaborative Research, 46 3.3 Revising STEM Education Will Facilitate Convergence, 53 3.4 Convergence May Contribute to Understanding Quantification and Reproducibility in Life Sciences, 56 3.5 Convergence Extends Beyond the Integration of Life Sciences, Physical Sciences, Medicine, and Engineering, 58 4 FOSTERING CONVERGENCE IN ORGANIZATIONS: CHALLENGES AND STRATEGIES 59 4.1 Convergence is Facilitated by Depth and Breadth of Expertise, 62 4.2 Diverse Perspectives Support Innovation, 64 4.3 Convergence Requires a Culture and Supporting Structures, 64 4.4 Convergence Intersects with Faculty Structures and Reward Systems, 69 4.5 Facilities and Workspaces Can Be Designed for Convergent Research, 77 4.6 New Education and Training Programs Can Be Developed to Foster Convergence, 80 4.7 Convergence Relies on Effective Partnership Arrangements, 84 4.8 Sustainable Funding is Necessary for Convergence Efforts, 87 4.9 The Convergence Ecosystem Includes Core Elements, 90 5 ADVANCING KNOWLEDGE AND SOLVING COMPLEX PROBLEMS THROUGH CONVERGENCE: CONCLUSIONS AND RECOMMENDATIONS 93 5.1 Conclusions and Recommendations, 94 5.2 National Coordination is Needed, 100 REFERENCES 107 APPENDIXES A Committee Member Biographies 115 B Workshop on Key Challenges in the Implementation of Convergence: Agenda and Participants 123 Convergence Of The Life Sciences With Fields Including Physical, Chemical, Mathematical, Computational, Engineering, And Social Sciences Is A Key Strategy To Tackle Complex Challenges And Achieve New And Innovative Solutions. However, Institutions Face A Lack Of Guidance On How To Establish Effective Programs, What Challenges They Are Likely To Encounter, And What Strategies Other Organizations Have Used To Address The Issues That Arise. This Advice Is Needed To Harness The Excitement Generated By The Concept Of Convergence And Channel It Into The Policies, Structures, And Networks That Will Enable It To Realize Its Goals. Convergence Investigates Examples Of Organizations That Have Established Mechanisms To Support Convergent Research. This Report Discusses Details Of Current Programs, How Organizations Have Chosen To Measure Success, And What Has Worked And Not Worked In Varied Settings. The Report Summarizes The Lessons Learned And Provides Organizations With Strategies To Tackle Practical Needs And Implementation Challenges In Areas Such As Infrastructure, Student Education And Training, Faculty Advancement, And Inter-institutional Partnerships. Committee On Key Challenge Areas For Convergence And Health, Board On Life Sciences, Division On Earth And Life Studies, National Research Council Of The National Academies. Includes Bibliographical References. This Project Was Supported By The Raymond And Beverly Sackler Science Fund Of The National Academy Of Sciences, The Burroughs Wellcome Fund, The Kavli Foundation, Research Corporation For Science Advancement, The National Science Foundation Through Grant Phy-1353249, The National Institutes Of Health Through Award Hhsn263201200074i/hhsn26300047, To#47, The William R. Kenan, Jr. Institute For Engineering, Technology & Science Of North Carolina State University, The Frank Hawkins Kenan Institute Of Private Enterprise Of The University Of North Carolina At Chapel Hill, And The Connecticut Institute For Clinical And Translational Science At The University Of Connecticut. The Views Expressed Herein Are Those Of The Authors And Do Not Necessarily Reflect The Views Of The Organizations Or Agencies That Provided Support For The Project. Front Matter ....Pages i-x Automated Detection of Central Retinal Vein Occlusion Using Convolutional Neural Network (Bismita Choudhury, Patrick H. H. Then, Valliappan Raman)....Pages 1-21 Swarm Intelligence Applied to Big Data Analytics for Rescue Operations with RASEN Sensor Networks (U. John Tanik, Yuehua Wang, Serkan Güldal)....Pages 23-54 Gender Classification Based on Deep Learning (Dhiraj Gharana, Sang C. Suh, Mingon Kang)....Pages 55-69 Social and Organizational Culture in Korea and Women’s Career Development (Choonhee Yang, Yongman Kwon)....Pages 71-84 Big Data Framework for Agile Business (BDFAB) As a Basis for Developing Holistic Strategies in Big Data Adoption (Bhuvan Unhelkar)....Pages 85-95 Scalable Gene Sequence Analysis on Spark (Muthahar Syed, Taehyun Hwang, Jinoh Kim)....Pages 97-113 Big Sensor Data Acquisition and Archiving with Compression (Dongeun Lee)....Pages 115-143 Advanced High Performance Computing for Big Data Local Visual Meaning (Ozgur Aksu)....Pages 145-164 Transdisciplinary Benefits of Convergence in Big Data Analytics (U. John Tanik, Darrell Fielder)....Pages 165-179 A Big Data Analytics Approach in Medical Imaging Segmentation Using Deep Convolutional Neural Networks (Zheng Zhang, David Odaibo, Frank M. Skidmore, Murat M. Tanik)....Pages 181-189 Big Data in Libraries (Robert Olendorf, Yan Wang)....Pages 191-202 A Framework for Social Network Sentiment Analysis Using Big Data Analytics (Bharat Sri Harsha Karpurapu, Leon Jololian)....Pages 203-217 Big Data Analytics and Visualization: Finance (Shyam Prabhakar, Larry Maves)....Pages 219-229 Study of Hardware Trojans in a Closed Loop Control System for an Internet-of-Things Application (Ranveer Kumar, Karthikeyan Lingasubramanian)....Pages 231-243 High Performance/Throughput Computing Workflow for a Neuro-Imaging Application: Provenance and Approaches (T. Anthony, J. P. Robinson, J. R. Marstrander, G. R. Brook, M. Horton, F. M. Skidmore)....Pages 245-256 Back Matter ....Pages 257-263