Prof. Zhengchun Liu
School of Physics and Electronics, Central South University, China
Research Area: sensing and intelligent instruments, microfluidic control chip and sensing, nano-drug loading and sensing, photoelectric materials and devices.
Title: In Situ Synthesis System for Polypeptide Biochip Based on Microfluidic Mixer
Abstract: Biochips have become a sophisticated analytical device in the fields of biochemical sensing and genetic analysis. However, the cumbersome preparation process and the high production cost limit the versatility of its application. Herein, we have developed an automated synthesis system for in situ preparation of biochip with peptide backbone based on the microfluidic mixer and micro reaction chamber. The microfluidic mixer was used as a key component to perform the real-time activation of the carboxylic groups, leading to an instant coupling reaction of monomers with high efficiency. The repeating synthesis procedure was realized without too much artificial participation with the help of flow control system based on programmable logical controller and LabVIEW. The real-time monitoring of synthesis process was realized with a low-cost solar cell coupled with simple ultraviolet absorption device. The practical capability performance of this synthesis system was further demonstrated by the synthesis of four cycles of aminocaproic acid, which indicated that this system may provide a new alternative for low-cost in situ synthesis of biochip.
Project:
[1] Construction of multifunctional carrier of chiral γ peptide nucleic acid and its effect on tumor cells in microfluidic chip, under research, National Natural Science Foundation of China, Zhengchun Liu
[2] Research on complete technology of SBS content detection of modified asphalt, conclusion, Hunan Provincial Department of Transportation, Zhengchun Liu
[3] Preparation of chiral γ peptide nucleic acid chip and its research on amplification-free unlabeled detection of double-stranded DNA, under research, National Natural Science Foundation of China, Zhengchun Liu.
[4] Research on preparation and application of high-density peptide nucleic acid chip, conclusion, National Natural Science Foundation of China, Zhengchun Liu
Dr. Santhosh Krishna
Department of Electronics and Communication Engineering at New Horizon College of Engineering, Bengaluru
Achievements:
[1] A project titled “RFID based shopping Trolley” has been selected as “Top 10 Best innovations in India-Shortlisted Winners” in the Innovation Jockey2 conducted by Accenture and Yahoo on 31st August 2013.
[2] Best Project Guide award by Institution of Engineers (IEI, India ) held on 6th -7th March 2015
[3] Best Project Award in National level by International Society for Scientific and Research & Development at ESIC 2014
Title: Development of Soft Computing based Bio-Inspired Algorithms and its impact on Practical System
Abstract: Historically, Industrial Automation and manage Systems (IAMS) were largely isolated from conventional digital networks such as enterprise ICT environments. Where connectivity was required, a zoned architecture was adopted, with firewalls and/or demilitarized zones used to protect the core control system components. The adoption and deployment of ‘Internet of Things’ (IoT) technologies is leading to architectural changes to IAMS, including greater connectivity to industrial systems. In this talk we will discuss on Industrial internet of things (IIoT) –its impact on the design of automation systems.
Assoc. Prof. Yajun Liu
School of Mechanical and Automotive Engineering, South China University of Technology, China
Research Area:
1. Mechanical system signal test, analysis, characterization, control and performance optimization
2. Mechanical system optimization design theory and automatic control technology for industry energy saving and emission reduction.
3. Manufacturing process mechanism and optimization control technology
Title: Adaptive controller parameter tuning : Based on deep reinforcement learning
Abstract: Adaptive control is suitable for solving control problems in time-varying systems. However, with the increase of the diversity of industrial products and the improvement of product stability requirements, the industry began to hope that the creation cycle of the control algorithm should be shorter. In recent years, data-driven controller design method has become a hot-spot in the field of controller design. This paper introduces an adaptive control algorithm parameter tuning method based on deep reinforcement learning, and the problem of constant speed control under variable load is studied. In the programming of the controller, shallow artificial neural network and error back-propagation mechanism are used to meet the performance requirements of the controller. The research highlights focus on the setting part of the initial value of the controller artificial neural network. In this part, the automatic adjustment of initial value of artificial neural network of controller is realized through the cooperative work of controller and computer, and the basic framework of computer side program is based on reinforcement learning algorithm. In this framework, by introducing network output noise, the researchers improve the exploration ability of parameter adjustment program, which provides the possibility to obtain global optimal parameters. The control program not only realizes the automatic design, but also has the strong ability to deal with the random load. Compared with the original PID control program, it can reduce the speed standard deviation by about 5%-10%.
Prof. Eckart Meiburg
Department of Mechanical Engineering University of California, Santa Barbara, CA
Introduction: Eckart Meiburg, Distinguished Professor of Department of Mechanical Engineering University of California, Santa Barbara. Also as director of Center for Interdisciplinary Research in Fluids, University of California. Received his Ph.D., Mechanical Engineering, University of Karlsruhe, with distinction. Dissertation topic: Numerical Simulation of the Formation of Two- and Three-Dimensional Structures in Shear Layers and Wakes in 1985. He have lots of professional societies member, such as fellow of American Physical Society, fellow of American Society of Mechanical Engineers, member of Society for Industrial and Applied Mathematics, member of EUROMECH Society, and member of American Geophysical Union. Service to the scientific community such as guest editor of special issue of the International Journal of Multiphase Flow, 2000-2002, editorial board, Book series on Environmental Fluid Mechanics, World Scientific Press, 2017 - present, etc.
Research Area: His research areas are fluid dynamics and transport processes, vortex dynamics, multiphase flows, sediment transport, environmental fluid dynamics, computational fluid dynamics, etc. Refereed more than 150 Journal Publications.
Title: Computational Sediment Transport
Abstract: I will discuss continuum-scale simulations of such large-scale phenomena as turbidity currents and river plumes. Such simulations can be employed, for example, in order to assess the hazards posed by sedimentary currents to submarine infrastructure, such as oil and gas pipelines. In addition, I will discuss grain-resolving simulations of small-scale flows that can be employed to derive constitutive equations for polydisperse, dense suspensions with and without cohesive forces.