Keynote Speakers

Prof. Chin E. Lin
National Cheng Kung University, Taiwan

Prof. Lin was born in Chang Hua, Taiwan. He received BS and MS from Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan, and Ph. D. of Electrical Engineering from Lamar University, Beaumont, Texas, USA. Since 1984, he has been with Department of Electrical Engineering, and Department of Aeronautics and Astronautics, National Cheng Kung University, from associate professor to full professor. Prof. Lin has wide research involvements on electric power engineering, power system economic dispatch, power electronics (as one of the early founders in Taiwan), new energy system, and then shifting into avionics systems, flight control, magnetic suspension system, and recent mobile communication and its added value applications in data communication and remote control. Prof. Lin has contributed more than 120 IEEE/AIAA/and other journal papers and more than 300 conference papers.

Prof. Lin has been serving academic positions as Dean and Head in National Cheng Kung University, Distinguished Chair Professor from South China University of Technology, Guangzhou, China, and presidents of Chinese Automatic Control Society, Taiwan, and International Association of Science and Technology for Development, IASTED, Swiss, as well as international conference organizing chairman, committee member, keynote speaker and session chair, also serving to many well-known international journals as associate editors and reviewers. Prof. Lin has received outstanding research award and several other awards from government funding.

Prof. Lin has been with very good relationship to industry for the past 35 years, and has established at least hundred cooperation programs to promote industrial research and development in products and manufacturing. Since 2002, Prof. Lin has been inspired with many new research concept and methodology as a member of "International Cooperation Program on Antimatters Search in Space", leading by Samuel Ting under support from NASA and 16 countries.

Speech Title: Airborne Robotics in Drone Applications

Abstract: Multi-rotor system is a kind of unmanned aerial vehicle (UAV). It is electrically driving in vertical take-off and landing (VTOL) maneuvering. System design, battery management, flight control, waypoint navigation for higher payload and longer endurance have been focused. Drone applications have been widely studied to fit for various environment and different missions. In the system design, multi-rotors have turned from quad-rotor into hexa-rotor or even octo-rotor as solutions to increase payload and endurance by integration of micro-electro-mechanical systems (MENS). It has become mature for use. This paper presents an airborne robotics in drone delivery for demonstration. A hexa-rotor drone is used by equipping with autopilot with GPS navigation and precision altitude control. In the flight operation, 4G mobile system is selected for communication to build into an embedded system for multiple drone control from ground base station. 4G mobile communication has better bandwidth for video streaming with less the 1.8 seconds lagging. Path planning follows Google map routing to fly over main streets to avoid ground obstacles, such as trees and buildings. An electronic geo-fence is created along flight route to ensure no hazard and collision. In altitude control, a high precision baro-height sensing maintains drones in 30 meters above ground during service. The altitude control also precisely checks vertical height to take-off and landing. Autonomous flight system controls the drone to start, climb, descend to deliver and return to base. The destination uses a QR code printout with assigned GPS for targeting to precise landing. To ensure the delivery being correctly accepted by the customer, a selfie face identification will be checked before releasing package. Mechanism for package releasing is designed and remotely controlled by ground base controller after face selfie. This work presents a full mission process for drone delivery from point to point under multiple drone operation from a ground base station. The autonomous drone delivery is successfully demonstrated from case studies. In this presentation, video recording for drone deliver will be played in real flight operations.

Prof. Houssain Kettani
Florida Polytechnic University, USA

Dr. Houssain Kettani received his Bachelor’s degree in Electrical and Electronic Engineering from Eastern Mediterranean University at Famagusta, North Cyprus, in 1998, and Master’s and Doctorate degrees both in Electrical Engineering from the University of Wisconsin at Madison, Wis., in 2000 and 2002, respectively.

Prior to coming to Florida Polytechnic University, Dr. Kettani served as a faculty member at: the University of South Alabama in Mobile, Ala., from 2002-2003; Jackson State University in Jackson, Miss. from 2003-2007; Polytechnic University of Puerto Rico in San Juan, Puerto Rico from 2007-2012; and Fort Hays State University at Hays, Kan. from 2012-2016. Dr. Kettani has also served as Staff Research Assistant at Los Alamos National Laboratory in Los Alamos, N.M. over the summer of 2000; Visiting Research Professor at Oak Ridge National Laboratory in Oak Ridge, Tenn. over the summers of 2005-2011; Visiting Research Professor at the Arctic Region Supercomputing Center at the University of Alaska in Fairbanks, Ala. over the summer of 2008; and Visiting Professor at the Joint Institute for Computational Sciences at the University of Tennessee at Knoxville, Tenn. over the summer of 2010.

Dr. Kettani’s research interests include computational science and engineering, high performance computing algorithms, information retrieval, network traffic characterization, number theory, robust control and optimization, and Muslim population studies. His research has been presented in over sixty refereed conference and journal publications and his work has received over four hundred citations by researchers all over the world. He chaired over 100 international conferences throughout the world, and has successfully secured external funding in millions of dollars for research and education from US federal agencies including NSF, DOE, DOD, and NRC.

Speech Title: Advances in High Performance Computing and Improvements on Monte Carlo Simulation Techniques

Abstract: In the past thirty years, advances in high performance computing have increased the performance by million times, and decreased the volume of the machine by similar order. Accordingly, the fastest computer in the world increased its performance from one Gigaflop/s in mid-1980s to a projected one Exaflop/s by 2020. In addition, current hand-held devices such as smartphones have performance that rivals those machines of the 1980s. Due to hardware limitations, parallel computing became an integral part of our lives that it is hard to imagine a device that is not using multiprocessor power, including smartphones. What started as a hardware solution to physical limitation, prompted software engineers to adopt to parallelism, which also motivates the theoretical solution to algorithms design and analysis to provide a solution that is parallel oriented rather than a serial oriented one. This in turn allows the use of more data points and more simulation trials to improve Monte Carlo simulations for better accuracy and smoother results.

Prof. R. Sivakumar
R.M.K. Engineering College, India

Professor Sivakumar is a Professor and Head of Department of Electronics and Communication Engineering at RMK Engineering College, Tamilnadu, India. He has been teaching in the Electronics and Communication field since 1997. He obtained his Master’s degree and PhD from College of Engineering Guindy, Anna University, Chennai. His research interests include Bio Signal Processing, Medical Image Processing, wireless body sensor networks and VLSI. He has published over 34 journal and 42 conference papers over the last several years. He has taught a wide variety of Electronics courses including Digital Image Processing, Multimedia Compression Techniques, VLSI Design, Medical Electronics and Electronic Circuits. Dr.Siva is a life member of the Indian Society of Technical Education, a member of IEEE. Dr. Siva has been invited to deliver Keynote Speech and Chair at various International conferences.

Speech Title: Medical Image Fusion using Stationary Wavelet Transform

Abstract: Medical image fusion involves combination of multimodal sensor images to obtain both anatomical and functional data to be used by radiologists for the purpose of disease diagnosis, monitoring and research. This presentation provides a comparative analysis of multiple fusion techniques that can be used to obtain accurate information from the intermodal MRI T1 T2 images. The source images are initially decomposed using Stationary Wavelet Transform (SWT) into approximation and detail components while the approximation components are reconstructed by Discrete Curvelet Transform (DCT), the SWT and DCT are good for point and line discontinuities. This paper also provides a comparative study of the different types of image fusion techniques available for MRI image decomposition. These approximation and detail components are fused using the different fusion rules. Final fused image is obtained by inverse SWT transformation. The fused image is used to localize the abnormality of brain images that lead to accurate identification of brain diseases such as 95.7% of brain lesion, 97.3% of Alzheimer's disease and 98% of brain tumor. Various performance parameters are evaluated to compare the fusion techniques and the proposed method which provides better result is analyzed. This comparison is done based on the method which provided the fused image with more Entropy, Average pixel intensity, Standard deviation and Correlation coefficient and Edge strength.

Plenary Speakers

Prof. Ming June Tsai
National Cheng Kung University, Taiwan

Prof. Tsai was born in Yin-Lin, Taiwan. He received MS from Department of Welding Engineering, and Ph.D. of Mechanical Engineering, both from the Ohio State University, Columbus, Ohio, USA. Since 1986, he has been with Department of Mechanical Engineering, National Cheng Kung University. He has been teaching Machine Design, Mechanical Design of Robotic System, Machine Vision, Screw Theory and Application, and Advanced Computer Graphics, etc. His previous research topics were on the applications of vision based robotic automation which includes robotic design, motion planning, off-line programming, and computer vision for 3D welding, mold polishing, and intelligent reverse engineering systems. The research topic is currently on the 3D body motion process technology. He developed an iBMPS software system that can create a personalized 3D digital body model to animate the body motions captured from this person. The body segment parameters (mass, centroid, and MOI) can be automatic computed and body motion analysis can be conducted very accurately. Now the recent research is focus on automatic body motion retargeting to all kinds of humanoid robots. The robotic systems designed and constructed by the Laboratory includes: (

1. Dual-mode 3D body scanning/motion capturing systems: D2000, D1680, D1400, D500. (The number after D- is the target height in mm)

2. 3D Body Scanners: AnnA (Anthropometry for numerous applications), projecting AnnA (P1400 for children), Portrator (for head), Peripher (for limbs).

3. Robots: ReapeR (Reverse engineering and automatic processing educable robots): ReapeR, AI-ReapeR, mini-ReapeR, super-ReapeR (all five axes robots), AMPS (automatic mold polishing system), AMRS (automatic mold recognition system), AWRS (automatic welding robotic system), 3 “Sunny” humanoid robots (with 31, 29, 17 axes respectively).

Prof. Tsai has been serving academic positions as Technical Committee of International Federation of Theory of Machines and Mechanisms (IFToMM) since 1991 as well as many international conference organizing committee member, keynote speaker and session chair. Prof. Tsai also received several awards from many institutions.

Speech Title: A Novel Definition of the ZMP via Screw Theory

A motivation on the fields of biomechanics and humanoid robots is to analyze the dynamic balance. Vukobratovic & Juricic computed the resultant ground reaction force on legged machines with no x- and y-moments, and the point was defined as the zero moment point (ZMP). Since then, ZMP has long been used for checking balance of legged robots.

A new screw-based approach has been proposed for calculating the ZMP of body motions. Using screw method, the body wrench screw $0 formed by the total body force FB and the inertial moment Min. A new coordinate system is constructed by locating the origin on the point that the axis of $0 passing through the ground (plane z=0) and putting the z axis along the axis of $0. According to the definition of the screw, only z-moment (no x- and y-moment) exists at any point along the screw axis $0. Then the new Origin naturally is the ZMP by the screw definition.

However, the conventional definition of ZMP is respect to the world coordinates, whereas the novel definition of the ZMP is according to the new frame with the z-axis align with the axis of $0. The validity of the proposed approach is demonstrated by evaluating the whole body dynamics over the course of a 25-second sequence of continuous motions performed by a professional martial arts practitioner. The results demonstrate that the magnitudes (forces/moments) of the body wrench screws are reasonable. Comparing the results obtained from the conventional method and the screw method for the ZMP locations over the 752 timeframes, the differences between two sets are small. Thus, two ZMP tracks nearly overlapped. The conventional ZMP definition is applicable for humanoid robots with big foot-print for stabilizing; whereas our ZMP definition is best suitable for body motion analyzing such as tiptoe contacting during ice skating, or ballet dancing etc. The screw-based ZMP definition would be a better method for tracking or controlling tiptoe dynamic balancing conditions without big foot-print as a conventional humanoid robot does.