December 14-15,2020



Conference Agenda

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Keynote Session:

Meetings International -  Conference Keynote Speaker Shigeru Omori photo

Shigeru Omori

Teikyo Heisei University, Japan

Title: Development of the laser-induced water bubble actuator


Shigeru Omori completed the Masters course from Graduate School of Electrical Engineering, Shibaura Institute of Technology in 1982. He joined Matsushita Denki Sangyo (c.k.a. Panasonic) in the same year. He was engaged in research and development of cathode ray tube and wavelength conversion device. He joined TERUMO Corporation in 1993. He was engaged in research and development of 3D television, micromachines, medical laser, and surgical manipulator at its R&D Center. He was a professor at Department of Medical Science, Faculty of Medical Science, Teikyo Heisei University in 2015. Presently, he is engaged in the development of medical laser and its application study. He is a Doctor of Medicine.


Aiming to realize the newly actuator without any electric cable, the use of laser-induced water vaper bubble has been proposed and performed the principle confirmation experiment. The laser induced water bubble has been applied for the liquid jet therapeutic catheter in medical field. The liquid jet system use physiologic saline for the liquid and a Ho: YAG laser of 2.1 µm wavelength that has highly absorption of water. Instead of this combination, we propose the use of carbon powder suspension for working liquid and an infrared Laser Diode (LD) of 970nm wavelength. As the 970nm LD light is not absorbed by water but carbon, the water of the working liquid could be vaporized by heated carbon. LD is considered as a suitable laser source for the actuator in the viewpoint of output controllability by the drive-current modulation. Figure 1 shows the conceptual image of the laser-induced water bubble actuator. It is constructed with a 970nm LD, an optical fiber and an actuator unit with working liquid for producing bubble.
An optical fiber connector (SMA connector) has been used for the bubble generator unit in our principle confirmation experiment. We use the inlet space for inserting and fixing fiber cable as the actuator cylinder. The working liquid was prepared by suspending carbon powder of 20µm particle size in water with surface active agent. After the working liquid has been injected in the cylinder, a stainless steel rod of Φ2.3mm diameter and 30mm length inserted as the actuator piston. When the laser irradiation was performed at the LD power of 160-180W and the pulse duration of 2msec, the reciprocating motions of the stainless steel rod have been observed.
For the next step, we are planning to evaluate the operating characteristic and also try to maximize the generating force.
This work was supported by JSPS KAKENHI Grant Number JP16K12914.

Meetings International -  Conference Keynote Speaker Qi Zhong photo

Qi Zhong

Zhejiang University, China

Title: Adaptive control for high speed on/off valve to preserve dynamic performance


Qi Zhong received the B.S. degree in Mechanical Engineering and Automation from Zhejiang University of Technology, Hangzhou, China, in 2010. He is currently working toward the Ph.D. degree in the School of Mechanical Engineering, Zhejiang University, Hangzhou, China. His research interests include digital hydraulic technology and its application in engineering machinery, intelligent control, and mechatronic systems.


High speed on/off valve (HSV) is an essential digital hydraulic component, and has been widely used for pressure and flow control in hydraulic systems, which require faster and more stable dynamic performance of HSVs to improve control preciseness. However, for some special kinds of HSVs, like ball structure and poppet structure valves which can reset by the hydraulic pressure instead of a traditional reset spring, their dynamic performance is greatly affected by the hydraulic pressure. Aiming at this problem, a self-correcting PWM control algorithm based on current feedback (SPWMCF) is proposed to improve and even maintain the HSVs’ original dynamic performance under changing pressures. Using current feedback analysis based on critical switching currents, the operational state of the HSV is estimated, and adaptive logic switching of different duty ratios of power source is also realized to preserve the dynamic performance of HSV under changing supply pressure to the maximum extent. Finally, a ball structure HSV is used as a research object, through numerical and experimental studies, it is demonstrated that the supply pressure has a great influence on the dynamic characteristics of the HSV, and the proposed control algorithm achieves the expected effect that the dynamic characteristics of the HSV is not only greatly improved but adapted to pressure changes, and the variation range of the dynamic performance can be controlled within 7.4% (0.3ms) under 4-20MPa operating conditions. The presented control algorithm is effective and can be applied in HSV-controlled systems to improve the robustness of the target actuator.

Meetings International -  Conference Keynote Speaker Brahm Pal Singh photo

Brahm Pal Singh

Panasonic Corporation, Japan

Title: High power terahertz radiation emitter and terahertz imaging technology


Brahm Pal Singh completed his Ph.D. in Quantum Electronics in 1990 from IIT Delhi, and D.Eng. in Quantum Engineering in 1996 from Nagoya University with Postdoctoral Studies at NPL New Delhi, India and AIST Tsukuba, Japan. Dr. Singh is a Research & Development Manager in Advanced Technologies Development Center, ES Company, Panasonic Corporation. He has published over 30 research papers in reputed journals and international conferences/symposiums and has been serving as a referee for the international reputed journals.


Terahertz (THz) radiations lie in electromagnetic spectrum gap between the infra-red and the microwave frequencies from 0.10 THz to 30 THz. In last few decades, generation and detection of THz radiations has attracted considerable interest not only in technological applications for THz imaging but also as a tool to investigate fundamental properties of materials by using time domain THz spectroscopy. Other applications too include information technology, biomedical sciences, non-destructive evaluation, security, quality control of foods beverage and medicines, environment monitoring and ultrafast computing etc. Much effort has been made to increase the generated terahertz radiation power. Among various methods, generation of THz radiation with the biased photoconductive switch (PCS), play very important role owing to its simple configuration and power controllability by bias and geometrical scaling. The low temperature (LT) grown GaAs PCS is most commonly used due to its sub picosecond lifetime and high mobility. Though, the THz generation efficiency is limited by its low breakdown field of about 5 x 105 V/cm. Thus, wide band gap materials with high breakdown electric fields are attractive for high power THz radiation, e.g., GaN with breakdown voltage 3.3 x 106 V/cm having high saturation velocity 2.5 x 107 V/cm and high thermal conductivity 1.3 W/cm K. Thus we investigate the most straight forward electromagnetic radiation from a GaN based large aperture LA-PCS. A carbon doped epitaxial layer was used for active region to realize high resistivity to stand high bias voltage.
THz pulses of 93.3 pJ/pulse energy was estimated at 500 V bias on excitation with 120 fs laser pulses of 266 nm wavelength with device structure as shown in fig.1. Figure 2 depicts the experimental setup with typical THz pulses and THz spectrum generated by LA GaN-PCS and measured with TDS detection.

Meetings International -  Conference Keynote Speaker Wataru Kase photo

Wataru Kase

Osaka Institute of Technology, Japan

Title: Polynomial matrix approach to the linear descriptor systems


Wataru Kase received his BE, ME and PhD degrees from Sophia University in 1985, 1987 and 1990 respectively, and joined the Dept of Information Engineering, Nagoya University, as a research associate. In 1996, he moved to the Dept of Electrical and Electric Systems Engineering, Osaka Institute of Technology, where he is currently a professor. His research interests include linear system theory, multivariable control systems and adaptive control systems.


The descriptor systems are convenient and natural modeling process for the practical plants. The state space method and the geometric approach are used to study the structure properties and to design the controllers. Comparing these methods, there are not so many literatures using the polynomial matrix approach. In this paper, we will propose an analysis method of the descriptor systems using the regularizing polynomial matrix. The regularizing polynomial matrix compensates the singularity of the descriptor systems, like an interactor matrix for rational function matrices. In fact, the regularizing matrix is almost equivalent to an interactor. Although some derivation methods of the interactor were proposed, almost of all were complex. Mutoh and Ortege proposed the algebraic equation, which the coefficient matrices of the interactor should be satisfied.  However, the solution method was not adequate for computer calculations. The authors proposed a solution of the equation using Moore-Penrose pseudo-inverse. Since a function to calculate the pseudo-inverse is available in some standard software for control engineering, the method is adequate for computer calculations.
We will show that the degree of the regularizing polynomial matrix presents a structural aspect of a given descriptor system. That is, there exists the regularizing matrix of degree one if a given system has no impulsive mode. There exists the regularizing matrix of degree two if a given system has some impulsive modes. We will also a condition for the impulsive controllability of the descriptor systems using the analysis. A method to stabilize the descriptor systems using the polynomial matrix approach will be given.

Oral Session 1:

  • Mechatronics|System Engineering|Microcontroller|Opto Mechatronics
Meetings International - Mech-2020 Conference Keynote Speaker Jayatu Sen Chaudhury photo

Jayatu Sen Chaudhury

American Express, India

Title: Machine learning applications in credit card domain


Jayatu Sen Chaudhury is the Vice President, Global Commercial and Merchant Data Science and Head of Enterprise Digital & Analytics India for American Express, India. Prior to this role, he was the Head of Global Information Management, Big Data Labs & Advanced Risk Capabilities. He has been a part of American Express since 2001, working in the various decision science functions for both US and international markets. He has earned his PhD in Financial Economics from IGIDR, Economic Research Institute funded by the Central Bank of the Country (Reserve Bank of India). Prior to joining American Express, he has worked in decision science for two years each in GE Capital and ICICI Bank.


Given the huge volumes of data available (both structured and un-structured) for American Express card members, American Express has adopted machine learning in all its core business processes of credit and fraud risk management, marketing analytics and operations. Work entailed building in-house data warehouses with right level of privacy controls and then using state of art machine learning algorithms from open sources to solve unique business problems across various business verticals. Adoption of machine learning has ensured building of robust economic models leveraging the best possible information, delivering the highest predictive power with utmost accuracy. The models are updated at the highest possible frequency ensuring the models incorporate the most recent information. This has led to significant improvement in the controls for fraud risk and also improved the targeting of appropriate segments with far higher accuracy in marketing. As a part of the presentation, 3-4 actual use cases of core American Express processes and how machine learning has completely changed the game will be discussed. Discussion will also include the new areas where company is thinking of doing research and bringing the best value for its card members.

Meetings International - Mech-2020 Conference Keynote Speaker Niladri Shekhar Dutta photo

Niladri Shekhar Dutta

Ericsson, UAE

Title: The advent of big data analytics in the world of ICT and digital


Niladri Shekhar Dutta is a seasoned professional with more than 13 years of global consulting experience. He is a Consulting Practitioner with focus on operations and transformation consulting for top-tier telecommunication operators globally. He has worked in more than 30+ consulting engagements in varied culture and markets across Western Europe, Middle East, North and Central Africa, India and New Zealand. His expertise is primarily around C-level advisory, digital transformation, digital enterprise architecture, business and operational process management, IT operational strategy, digital risk and revenue management consulting. He is responsible for driving consulting business across the MEA region for Ericsson and is involved in both sales and delivery. He has his MBA in Marketing and Finance from Symbiosis, Pune, India and is an Engineering graduate in Electronics from University of Nagpur, India. He is presently also undergoing a specialized PG program from MIT Sloan and Columbia facilitated by Emeritus on Digital Business.


With the advent of technology transformation in the fast-changing and ever-evolving world of Information, Communications and Technology (ICT), the importance of data is supreme. This is often being referred to as big data and is perhaps the single most entity which forms the backbone of any major transformation within any large global corporation across industries. Data is no longer being looked and used as a tactical medium for storage or operations; on the contrary, it becomes extremely strategic in nature. In fact, the 3 main pillars of today’s disruptive world of digital are driven by big data, IoT, and cloud. Out of which big data is the nucleus of transformation. In the world of digital, this is very well centered on three main life cycle entities. They are the customer, the product, and the revenue. Each of these, i.e. customer life cycle, product lifecycle and revenue life cycles behave very differently from one another. The practical emphases of data in each of these entities are also very different and unique. The concepts of big data within these 3 life cycles are core to the change we witness in the world of digital. Each data entity centered on these life cycles is instrumental in C-level decision making and major change management that happens within the organization. The data element acts as a central aspect to strategic decisions whether it comes to new product/service development or behavior of customer or user data, appreciation or acknowledgement of revenue. All use cases around big data will be largely centered on these and any specific case would be a secondary derivation of the above. With big data being so strategic in nature a large part of the focus has now shifted to data extraction and normalization to ensure meaningful information is extracted and utilized for business benefits by customers. Like the traditional mindset used to be, focus was largely around data operations and reporting. We will soon see a world where we cannot live without any form of data and in truest sense the phrase big data would essentially be big and superimposed in all aspects of our lives, right from our behavior, buying and consumption of products and services to distribution of our resources. The extraction and transformation of data for key benefits will be very much a business, as usual, thing, without which survival will become questionable within ICT industry, especially whilst looking at the concept of digital disruption. This article largely focuses on the key aspects of the same within the world of ICT and how a corporation is heavily dependent on such aspects for generation of its sales and management of its operations.

Meetings International - Mech-2020 Conference Keynote Speaker Tilila El Moujahid photo

Tilila El Moujahid

Microsoft Corporation, UAE

Title: Using genomics cloud platform and machine learning for genome variant analysis


Tilila is currently a Data Scientists and a Technical Evangelist for data and AI working at Microsoft. She accompanies partners in architecting and building their
cloud based, AI powered solutions. She was previously a Technology Strategist for enterprise accounts including Education and healthcare industry. She’s also a Fulbright scholar who earned, in 2012, a master in Computer Science and Business from San Francisco State University where her focus was on Bioinformatics including Genomics and Biomedical Image Analysis.


Next Generation Sequencing (NGS) allows performing massively parallelled DNA sequencing and is currently revolutionizing biological studies. Instead of sequencing a specific set of genes solely, NGS allows to sequence a wider portion of the genome (even a whole genome), which opens the door for a wider analysis of biological pathways within an individual. Researchers have never before accessed such a wealth of genomic data which holds the promise of unvealing the secrets of the most daunting deseases of the century such as cancer. It also comes with its own set of challenges for the management and analysis of Big Data to extract meaningful and actionable insights. Cloud computing and machine learning do have the capacity to solve this challenge. In this talk we will show how Cloud-based Genomics platform allows to manage petabytes of genomic data as well as foster fast and agile Secondary Analysis. We’ll also also use genomics specific machine learning packages to perform Tertiary Analysis on gene variants data and visualization tools to expose and share the results with the scientific community. We will begin the talk with the introduction to the genomics field and the commonly used genomic analysis process and will present practical applications of the above services and analysis.