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 SPEAKER
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: (http://www.bodymotion.myqnapcloud.com).
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
Abstract: 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.