KEYNOTE SPEAKERS
Ian Petersen
Australian National University, Australia
Keynote Speech Title:
Using Systems and Control Theory Ideas in the Design of Quantum Amplifiers
Abstract:
One of the most significant areas emerging in the area of quantum technology is that of quantum computing. Companies such as Google, IBM, and Microsoft have made significant investments in quantum computing to develop small scale quantum computers using microwave frequency technologies involving arrays of superconducting Josephson junctions operating at millikelvin temperatures. Other technologies which have been investigated for the implementation of quantum computers include quantum optics, ion trap devices and solid state quantum technologies. Quantum amplifiers play a critical role in many of these quantum computing technologies in that they are required to read out qubit states and transfer the information to the classical world.
Quantum amplifiers are examples of linear quantum systems and can be analysed using the recently developed theory of quantum linear systems. We begin with an introduction to quantum linear systems theory including the concept of physical realizability. We then present a systems theory approach to the design of quantum amplifiers minimizing the amount of quantum noise introduced by the amplifier whilst still guaranteeing desired properties of the amplifier such as the phase-insensitive property and the non-reciprocal property. We also consider the achievable gain and bandwidth of quantum amplifiers. These methods can be applied to amplifiers implemented using a quantum optics technology or a superconducting microwave technology. Our approach is based on a singularly perturbed quantum system involving the broadband approximation of a Bogoliubov transformation. In the case the optical implementation of a phase-insensitive amplifier it requires two squeezers and two beamsplitters. In the case of the optical implementation of a non-reciprocal and phase-insensitive quantum amplifier it requires three squeezers and two beamsplitters.
Homepage:
Toshio Fukuda
Meijo University, Japan, and the Beijing Institute of Technology, China
Keynote Speech Title:
Micro and Nano-robotic Manipulation and Applications
Abstract:
The micro and nano robotics technology has been studied for last two decades and has been applied for many sectors, such as industrial and academic applications. The modern industrial products can have many advantages of accuracy, efficiency as well as low cost productions, while the academic areas have many cutting edges technology applications to many advances research fields, such as nano-materials, nano-devices such as sensnor and actuator, bio medical applications and life sciences:
- 3D manipulation and assembly:
Carbon nanotube (CNT) as well as graphene was manipulated by the Nano robotic manipulator for pick and place like regular robotic manipulator and further bend, cut and soldering by EBID for the 3 D assembly. Graphene is also manipulated as folding like “Origami” by nano-robotic manipulation.
- Bio Cell characterization by Nano manipulation
Bio-cells can be characterized by examining, screened and cultivated using the micro- nano robotic manipulators, by which the cell Young Modulus and stiffness were measured by Nano-robotic manipulation system. Cell bio-viability can be tested and evaluated by the nano-robotic system.
- 3D Cell Bio-Assembly
Bio cells as assembled by micro and nano-robotic manipulation systems to form patterns and make various 3D structures. make 3D structures.
These bio-assembler by robotic technology is a very important tool for the bio-nano cell surgery and tissue engineering.
Homepage:
Wei Xu
Huazhong University of Science and Technology (HUST), China
Keynote Speech Title:
Efficiency Improvement for Linear Induction Machine and Drive System Adopted for Urban Transportation
Abstract:
Urban transportation, e.g. linear metro, driven by linear induction machine (LIM) has been paid much more attention both by academic and industrial communities recently for its direct thrust drive, strong climbing ability, flexible line choice, smaller cross-section area, lower noise, etc. However, this system suffers greatly to lower working efficiency in comparison to the rotary IMs due to its cut-open primary (end effect), vertical force resulted from the asymmetric structure, and so on. There exists great difficulty for accurate modeling for LIM influenced by nonlinear circuit and partial magnetic saturation. This speaking will discuss different ways to increase the working efficiency of LIM and drive from design and control. Furthermore, some emerging techniques, like system-level optimization methodology on LIM and drive will be discussed briefly.
Homepage:
Zhiyong Chen
The University of Newcastle, Australia
Keynote Speech Title:
Secure Networked Control of Large-Scale Cyberphysical Systems Using Cryptographic Techniques
Abstract:
We present a secure environment for networked control systems composed of multiple dynamic entities and computational control units via networking, in the presence of disclosure attacks. In particular, we consider the situation where some dynamic entities or control units are vulnerable to attacks and can become malicious. Our objective is to ensure that the input and output data of the benign entities are protected from the malicious entities as well as protected when they are transferred over the networks in a distributed environment. Both these security requirements are achieved using cryptographic techniques. However, the use of cryptographic mechanisms brings additional challenges to the design of controllers in the encrypted state-space; the closed-loop system gains and states are required to match the specified cryptographic algorithms. We propose a methodology for the design of secure networked control systems integrating the cryptographic mechanisms with the control algorithms. The approach is based on the separation principle, with the cryptographic techniques addressing the security requirements and the control algorithms satisfying their performance requirements. This talk presents the design of private controllers for two typical control problems, namely stabilization and consensus, as well as the discussion of numerical simulations and results.
Homepage:
Latifur Khan
The University of Texas at Dallas, USA
Keynote Speech Title:
Data to knowledge: Modernizing political event data, social media data and covid19 images using machine learning (ml)
Abstract:
We have developed the software and big data infrastructure to provide machine coded event data from news reports from historical and real-time inputs from the web. The project is ongoing and will produce coded news reports based on Natural language processing (NLP) applications across English, and Spanish news reports. Human annotations and validations are conducted for data validation and cross-lingual support. Geo-location of the events is also improved for better spatial resolutions. One of the main computational challenges we address in this work is related to the efficiency and scalability of parsing online news articles in real-time. In particular, we designed a distributed system with Apache Spark and Kafka to process large amount of news articles for event coders and the actor recommender system. This system processes articles in near real-time while generating events which are provided to end-users using our REST API at http://eventdata.utdallas.edu.
We are developing tools to scrap data from social media (Twitter) to extract actionable information to support first responders for Road traffic injuries (RTI) victims in low and middle-income countries. In the long term, this tool will provide new, low-cost technology based on semi-supervised learning that provides simple, accurate and reliable methods to improve the timeliness and accuracy of RTI reporting, shorten response times, and enhance triage decisions by first responders. We will demonstrate how this novel semi-supervised learning techniques can be applied to Covid19 image classification.
The event coding work is a collaborative effort with political scientists at UT Dallas, Dr. Patrick Brandt and Dr. Jennifer Holmes, funded by NSF. The extraction of actionable information from social media is collaborative work with the University of Texas Southwestern Medical Center (UTSW), funded by NIH.
Homepage:
Celia Shahnaz
Bangladesh University of Engineering and Technology, Bangladesh
Keynote Speech Title:
Automation for Disease Detection from 1-D and 2-D Biosignals based on Signal Processing and Deep Learning
Abstract:
Computer-based automatic reduction of noise and detection of abnormality is time-saving, and more accurate. Among various 1-D biological signals, ECG and EEG are important to diagnose cardiac arrhythmia and Seizure detection. To treat the diseases or injuries of the joints, bones, muscles, and spine in both adult and pediatric imaging the 2-D musculoskeletal radiographs bring a significant depth of expertise. Numerous methods have been reported to denoise ECG signals. The investigation and detection of seizure and epilepsy can be easily performed from the behavioral actions of the brain recorded by the EEG. Various machine learning processes have played a significant role in medical image classification and abnormality detection from musculoskeletal radiographs. In this talk, ECG denoising approach based on noise reduction algorithms in empirical mode decomposition (EMD) and discrete wavelet transform (DWT) domains will be discussed. EEG signals of seizure and non-seizure activities will be discussed and classified into five groups on the basis of seizure onset, seizure action and brain signal recording location based on bimodal Gaussian modeling of the gamma and theta band IMFs of EEG signals. Deep learning models, such as Capsule network architecture will be explained here for musculoskeletal radiographs abnormality detection.
Homepage:
S. M. Muyeen
Curtin University, Australia
Keynote Speech Title:
State-of-the-art Research Facilities in Educational Institutes for Sustainable Energy Growth
Abstract:
Sustainable energy technologies are rapidly changing nowadays. The emphasis is now strongly focused on Renewable Energy, and its grid connections, micro-grid, layered communication enabled power infrastructure and protection systems. Hence, power engineering research is going through a major transformation around the world. There was a gap in power system research for a sustained period due to the development in some emerging technology, including computer, telecommunication, and the internet. IoT applications are now just a concept but a reality. Future jobs for power engineering graduates and their career largely depends on learning the new game prior to joining the workforce. Universities are training ground for them and must change the way they are currently teaching power engineering. To mitigate, many universities and research centers invested in power and energy laboratories to boost the research and development in renewable sectors and smart grid area. These laboratories have setups for wind turbines (fixed and variable speeds) testbed, photovoltaic system, fuel-cell, energy storage systems, marine current/tidal plants, etc., blending power and control hardware-in-the-loop facilities. There also exist some hardware/software platforms from different vendors, which helps in understanding power system operations starting from generation, transmission, and distribution. Students now can easily visualize the actual systems using these facilities, which eventually wide-spreading power systems and renewable energy research. This talk is dedicated to discussing recent successes and future needs/trends of laboratory facilities in advancing sustainable energy research across the world.
Homepage:
Mariofanna Milanova
University of Arkansas at Little Rock, USA
Keynote Speech Title:
Visual Intelligence and Deep Learning models: What we can learn from hierarchies in the primate’s Visual Cortex?
Abstract:
Will be published soon!!!
Homepage:
https://ualr.edu/computerscience/faculty-and-staff/mariofanna-milanova/
Raad Raad
University of Wollongong, Australia
Keynote Speech Title:
Will be published soon!!!
Abstract:
Will be published soon!!!
Homepage:
Prahlad Vadakkepat
National University of Singapore, Singapore
Keynote Speech Title:
Industry 4.0 – AI, Robotics and Automation
Abstract:
The fourth industrial revolution, namely Industry 4.0, is a buzz word lately. Industries have established R&D processes, plant operations, supply chains and technologies. Now the industries need to change and improve the sets of processes to remain competitive. Industry 4.0 is a broad term involving modern technologies and processes that can integrate, replace or improve legacy technologies and processes leading to improved productivity. With improvements in productivity and efficiency, the carbon footprint will reduce which in turn will contribute towards sustainability.
Internet of Things, Artificial Intelligence, Robotics and Automation are transforming industries to cyber physical systems. With historical data and insights along preventive maintenance, the entire production line can be visualised, and decisions can be taken autonomously. When industries embrace the Industry 4.0 transformation, skill sets in AI, IoT, Robotics and Automation will dominate, while certain typical job profiles ceasing to exist in the next 5 or 7 years.
Increased awareness about Industry 4.0 and sustainability is essential and school curricula need changes to prepare graduates who are future ready. It is hoped that AI, IoT, Robotics and Automation will contribute towards paving the way for a better tomorrow for all. This talk will focus on Industry 4.0 related technologies and the challenges faced by Industry and ahead. That in turn can highlight the need for changes academia and research to prepare for a unique tomorrow.