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5th EAI International Conference on Big data and Cloud Computing Challenges

March 8–9, 2018 | Chennai, Tamilnadu, India

 

Dr. Anu A. Gokhale

Dr. Anu A. Gokhale has completed twenty-five years of university teaching and is currently a professor and coordinator of the computer systems technology program at Illinois State University. She is named Fulbright Distinguished Chair in STEM at the University of Pernambuco, Brazil, 2016-17; was a Faculty Fellow in Israel and Fulbright Specialist in cybersecurity at Gujarat Technological University, India in summer 2017; and a Visiting Professor at Shandong University in Jinan, China during spring 2017. Dr. Gokhale was honored with the 2011 University Outstanding Researcher Award. Originally from India, she has a master’s in physics‒electronics from the College of William & Mary, and a doctorate from Iowa State University. She presents and publishes her peer-reviewed research, and pursues multi-year projects funded by agencies like the US Department of Education, US Department of State, and National Science Foundation. The current NSF funded project is in Computing Education for the 21st Century. Dr. Gokhale authored a second edition of her book Introduction to Telecommunications, which has an international edition in Chinese. She continues to be an invited keynote speaker at various conferences, latest ones include: 2017 International Conference on Knowledge Engineering and Applications, London, UK; 2016 International Conference on Communication and Information Systems, Bangkok, Thailand; 2015 International Conference on Information Technology, Amman, Jordan; 2014 International Conference on Control, Robotics and Cybernetics, Singapore; and 2013 International Conference on Advanced Computer Theory and Engineering in Maldives. She consults for businesses and has delivered multiple workshops. As an active volunteer in IEEE, she has served as R4 Educational Activities Chair, Women in Engineering Coordinator, Chair of International Electro/Information Technology 2010 Conference, and MGA representative to the Educational Activities Board. She was honored with the IEEE Third Millennium Medal.

TOPIC: Cloud-Stored Big Data Analytics – A Survey of Algorithms

ABSTRACT

The explosion in data resulting from social, mobile, and cloud computing technologies has created new challenges, and they are being converted into opportunities by the scientific community. Knowledge discovery in database is the application of analytical procedures to extract more insight from multiple formats of data that is captured through various means. Powerful tools for finding anomalies, implicit patterns, and correlations in large volumes of both structured and unstructured data are being investigated. The unstructured data and intangible components like intent and sentiment are difficult to analyze but have untapped potential that would enable comprehension of underlying cognitive processes. The talk will discuss several algorithms and techniques being used to extract knowledge hidden in cloud-stored information, and use it to make data-driven decisions.


 

Dr. Balan Sundarakani

Dr. Sundarakani is an Associate Professor and Program Director for Master of Science in Logistics in the Faculty of Business and Management at the University of Wollongong (Australia) in Dubai. Previously he was working as an Assistant Professor with UOWD from May 2009 till Aug 2011. He has 12 years of teaching and research experience in the area of Supply Chain Management across the various universities including the National Institute of Technology, Tiruchirappalli, IIT, Roorkee, Hindustan University, Chennai and the National University of Singapore, Singapore. He also served as an Adjunct Research Fellow with the Chair of Logistics Management with Swiss Federal Institute of Technology (ETH), Zurich, Switzerland. 

Role of Big Data analytics in Supply Chain management

Big data is increasingly becoming a major organizational enterprise force to reckon in this global era for all sizes of industries. The use of big data tools and methodologies has become an imperative for businesses leaders across every industry sector and also plays a significant role to improve operational and strategic capabilities. Hence, it has become vital for managing supply chain functions, where data intensive processes can be vastly improved through its effective use. However, decision making in a modern supply chain environment is a complex process. A large number of manufacturing and service organizations are therefore seeking expert systems that can help to identify, sort, clean and develop strategies  that can be deployed in supply chain decisions. There exist an untapped potential from enterprises where they need some specialized architecture that can control big-data supply chain and to develop strategies through data sharing among multiple stakeholders. This research propose a novel architecture  for big-data driven supply chain environment, which support to visualize the data that are processed in the  five supply chain stages which could be used for industry environments. 


Privatdozent Dr. rer. nat. habil. Sven Groppe

University of Lübeck

Institute of Information Systems (IFIS)

Lübeck, Germany

 

 

 

 

 


Dr. Ernest Fokoue, 

Associate Professor

Centre for Quality and Applied Statistics

Rochester Institute of Technology, USA



Dr  João Manuel R. S. Tavares, MSc, PhD, Habilitation

Faculty of Engineering, Department of Mechanical Engineering

University of Porto

Rua Dr. Roberto Frias, s/n , 4200-465 PORTO, PORTUGAL


Dr. Kavi Mahesh

Director

KAnOE Centre for Knowledge Analytics and Ontological Engineering

Bangalore, India


 

Professor Henry B.L. Duh, PhD (Washington), FIET, FBCS, SMIEEE, SMACM

Head, Department of Computer Science and Information Technology College of Science,

Health and Engineering BG 243 La Trobe University,

Melbourne Victoria 3086 Australia

 

 

 


Dr. Selwyn Piramuthu,

Professor of Information Systems, University of Florida,

Gainesville, Florida, USA

Selwyn Piramuthu is Professor of Information Systems at the University of Florida, where he has taught since Fall 1991. Trained in machine learning, his research interests also include cryptography with applications related to IoT/RFID, privacy/security, supply chain management, among others. Co-authored with Wei Zhou, his book titled, “RFID and Sensor Network Automation in the Food Industry” was published by Wiley in 2016. He received his B.Tech., M.S., and Ph.D. respectively from IIT-Madras, University of Arizona, and University of Illinois at Urbana-Champaign.

Title of the Presentation: Big Data in IoT Applications
Abstract: As IoT (Internet of Things) adoptions become widespread with a concomitant increase in the number of applications, there is a need to take account and consider what has been realized and what could be improved. One such facet is associated with the automated generation of data in such IoT-based systems.  With the unprecedented explosion in generated data, it becomes necessary to identify usable patters and to use them for actionable intelligence. We discuss some of the characteristics of such data and their analyses.