The 1st Univ. Carthage – Hosei International Joint

Webinar with honorable support by
the Embassy of the Republic of Tunisia in Japan

Recent Issues in, Intelligent Robotics, Machine
Learning and Distributed System
March 17th (Wed), 2021
This webinar introduces advanced research projects on intelligent robotics, Machine
Learning and Distributed System under the joint auspices of the engineering faculties
of University of Carthage and Hosei University, IIST: Institute of Integrated Science andTechnology, to promote international research and educational collaboration among theiraffiliated schools.

AgendaZOOM ID
https://hosei-acjp.zoom.us/j/86357937413?pwd=c3NITXFEUVRKSHFqeHZvdGVxa0dOUT09
Meeting ID: 863 5793 7413
Pass Code: carthage&h
OPENING REMARKS
2021/3/17, 08:00-08:15(UTC),09:00-09:15 (CET), 17:00-17:15 (JST)Mr. Fethi JELASSI, Counsellor, Embassy of the Republic of Tunisia in Japan
Dr. Mongi BESBES, Vice-President, University of Carthage.
Dr. Kazuo YANA, Director of IIST, Hosei University,
SESSION 1 (Presentation, 20min, Q&A 10min. all together)
University of Cartage RESARCH PROJECTS
08:15-9:25 (UTC), 09:15-10:25 (CET), 17:15-18:25 (JST)1

1-1 Syrine Ben Yehia, Neila Bedioui,”PID Haptic Robot Control For Teleportation”
1-2 Eya Labidi, Zied Tmar,” Suitable Observer-based Control of Omnidirectional Mobile
Robots”
1-3 Neila Bedioui, Mongi Besbes,” Adaptative Control of VTOL”
Q&A
INTERMISSION (20 min.)Coffee Break with Demonstration of INSTM(Carthage) and IIST(Hosei)
09:25 – 09:45 (UTC), 10:25-10:45 (CET), 18:25-18:45 (JST)SESSION 2 (Presentation, 20min, Q&A 10min. all together)
IIST RESEARCH PROJECTS
09:45 – 10:55(UTC), 10:45-11:55 (CET), 18:45-19:55 (JST)2-1 Akihiro Fujii, “Discussion about an anonymous and trusted communication
environment”
2-2 Xiang Kun, Akihiro Fujii,”Reputation Analysis Based on Weakly-Supervised BiLSTM-Attention Network”
2-3 Shunsuke Kitada, Hitoshi Iyatomi,” Practical and Interpretable Deep Learning

Techniques in our Iyatomi's Lab”
Q&A
CONCLUDING REMARKS
10:55-11:00 (UTC), 11:55-12:00 (CET), 19:55-20:00 (JST)Dr. Jinjia Zhou, Assoicate Professor of Applied Informatics, Hosei University

Proceedings(draft)
1-1 PID Haptic Robot Control for Teleportation
In the past few years, a new scenario for robot-based applications has emerged. Service and mobile
robots have opened new market niches. Also, new frameworks for shop-floor robot applications havebeen developed. In all these contexts, robots are requested to perform tasks within open-ended
conditions, possibly dynamically varying. These new requirements ask also for a change of paradigm
in the design of robots: on-line and safe feedback motion control becomes the core of modern robot
systems. Future robots will learn autonomously, interact safely and possess qualities like selfmaintenance. Attaining these features would have been relatively easy if a complete model of theenvironment was available, and if the robot actuators could execute motion commands perfectly
relative to this model. Unfortunately, a complete world model is not available, and robots have to planand execute the tasks in the presence of environmental uncertainties which makes sensing an importantcomponent of new generation robots. For this reason, today's new generation robots are equipped withmore and more sensing components, and consequently they are ready to actively deal with the highcomplexity of the real world. Complex sensorimotor tasks such as exploration require coordination2

between the motor system and the sensory feedback. For robot control purposes, sensory feedback
should be adequately organized in terms of relevant features and the associated data representation.
There is a compelling case for using principles of human haptic perception—active touch—to inspire
the development of robot haptic systems. Human haptic exploration is efficient, robust to noise, yet
adapts rapidly to changing conditions. Moreover, human hand control is the archetypal generalpurpose sensorimotor system. It uses biological mechanisms to achieve a remarkable degree offunctional flexibility, across huge variations in conditions, that remains elusive in “intelligent
machines.” Key to this capability (over-and-above the hand's anatomy) are the neural control processes
underlying hand function. It is valuable therefore to consider the approaches taken to robot haptics,
and the main challenges, in light of these “organizational principles” of human hand control.
Haptics provides useful information under a wider set of circumstances than is sometimes appreciated.
First, and most obviously, haptics can be the only available signal, such as in poorly lit environments,
or when reaching into a bag. Second, even when other senses are available, haptics provides direct
information about properties of objects that are poorly (or at least very indirectly) specified by othersenses. This is because haptics, uniquely among human senses, involves physical interaction with
objects, allowing properties such as friction and compliance to be sensed. Third, haptics contributes
to sensorimotor processing even when it provides redundant information to other senses.
The active nature of haptics presents key challenges to haptic-sensing robots. It is necessary to
determine not only what the properties of the sensors should be, but also what information is required
in a given situation, and which actions should be performed to elicit it. Gibson (1950) described active
perception in the context of vision, noting that optic flow signals to observer motion and the structureof the environment are acquired by an observer who moves, and therefore directly influences theacquired information.

the realization and the implementation haptic systems, either in "virtual reality" or in remote handling,mobilize skills strongly multidisciplinary, disciplines summarized in the diagram opposite (note thatthe technological disciplines opposite (*) are not isolated from each other but behave well obviouslytransversal skills to varying degrees). More and more users of haptics numerous and for more andmore uses diversified: PC gaming, simulators (aeronautics, military, surgical, dentistry, etc.),
telerobotics (dangerous environment, medicine, ...)

3

ROBOT HAPTIQUE SET
The haptic robot proposed by SET can be used as a haptic interface but we can also create a remotemanipulator, by associating two remote robots, one as master and one as slave. The design of thishaptic robot is of the "delta robot" type, that is to say with a parallel structure with 3 chains identicalclosed kinematics connecting the base to the removable terminal organ (effector), offering 3 degrees
of freedom in translation. Each kinematic chain has a motor and an incremental encoder.

Disturbance Observer-based Robust Control
Robust motion control (e.g., position, force and compliance control) has been one of the most popularapplication areas of DOb since 1980s. The 2-DoF robust controller was applied to the motion control
problem of many different engineering systems, spanning from industrial robots, hard-disk drives,automobiles and Hubble Space Telescope to today’s cutting edge robotic systems such as compliant
exoskeletons, surgery robots and unmanned aerial vehicles . It was shown that a DOb can be used not
only to achieve the robustness of a motion control system but also to estimate contact force/torque asa force sensor. This specific application of DOb is known as Reaction Force Observer (RFOb) in the4literature, and it has been verified in many different engineering applications, e.g., in rehabilitation
robotics, electric commuter trains and automotive. As a robust motion control tool, DOb has been
rapidly matured in the last three decades. Today, DOb-based motion control products are commerciallyavailable in the market, and new motion control products keep being developed. In addition to motion
control, DOb has been applied to several applications in different research fields. For example, robotic
eye-hand calibration, robust control of mineral grinding process, time delay estimation andcompensation of network control systems partial synchronization of neurons , sensorless measurementof pulsatile flow rate [103], temperature control of a superheated steam, and feedback linearization
control of a nuclear reactor. Since plant dynamics are more complicated than servo systems, nonlinear
nominal plant models and advanced performance controllers, such as nonlinear and iterative learning
controllers, have been generally employed in the design of the robust controllers. Although theperformance controller and DOb can be independently synthesized thanks to the flexible structure of
the 2-DoF control method, the analysis and synthesis of the advanced robust controllers are generally
complicated. In the last three decades, DOb-based robust control has inspired many researchers.
Several linear and nonlinear observer-based robust controllers have been independently developed in
the literature. For example, the robust controllers based on: Perturbation Observer (PO), Equivalent
Input Disturbance (EID) estimator, Uncertainty and Disturbance Estimator (UDE), Generalized
Proportional Integral Observer (GPIO), Extended State Observer (ESO) and Extended High Gain
Observer (EHGO). In these robust control systems, the fundamental idea behind the controller
synthesis is same as the DOb-based robust control system: estimating the internal and external
disturbances by using the known dynamics and measurable states of a system (i.e., disturbanceobserver synthesis), feedbacking the estimations of disturbances so as to intuitively achieve therobustness of the control system (i.e., disturbance cancellation/suppression) and tuning theperformance controller by considering the nominal plant model (i.e., 2-DoF control).

Dr Neila Bedioui
PhD on Electrical engineering at ENIT, Master Degree on
Automation and signal treatment at ENIT, Engineering degree
on Electrical Engineering at ENIT, Director of study andinternships at ISTIC(since December 2020), Director ofindustrial computer department
at ISTIC(2016-2020),
Research Fields: Robust control, observer design,
LMI,
Embedded system, PSOC,VHDL,
Mrs Cyrine Ben Yahya,
2018:Research master's degree in Robotics, Computer andCommunication Systems (M1), 2014: Fundamental Licenses inElectronics Electrotechnical and Automatic, End-of-studies
project: Realization of a stand-alone single-phase inverter with
PWM control ,2014: Summer internship: Industrial practical at
TRADETEK, 2013: Summer internship : Office tasks in a
maintenance department5

1-2 Suitable Observer-based Control of Omnidirectional Mobile Robots”
In field of mobile robots, the class of omnidirectional mobile robots (OMRs) can perform
both translational and rotational motion simultaneously and independently permitting
them to have an arbitrary motion in an arbitrary orientation without changing thedirection of wheels. High maneuverability and flexibility promote the wide applicationsof OMRs. Compared with non-holonomic mobile robots, OMRs are particularly adapted
to little working spaces, like warehouses, some factories and hospitals.
The trajectory tracking control of OMRs plays an important role in robot applications,
it consists to control the robot in real time to track a reference trajectory, an accurate
track is always one of the important objectives fixed by researchers. In the literature,
there have been a lot of works on the trajectory tracking control of OMRs, such as
trajectory linearization, adaptive sliding-mode, model-predictive, switching-parametervarying, active disturbance rejection, extended and state observer.
However, in real applications, the control design has several problems. For example,
one worrying problem in the observer-based methods is the initial peaking phenomenon.
This is due to the large initial estimation error of the observer. It will considerably
decrease the control performances and may cause the damage of motors or mechanisms.
Furthermore, in practical applications, affected by complex and changeable operating
conditions and environmental parameters, it’s usually difficult to meet the highperformance control requirements using a traditional control.
In our case, we intend to design a nonlinear observer-based structure trajectory
tracking scheme, suitable to an OMR like Robotino. Firstly, we need to establish thespecific OMR state model by reviewing the existing proposed models in the previous
literature works, and verify all imposed assumptions in order to take into considerationsome other prospective parameters or nonlinearities. A set of possible adapted or pseudoadapted observers developed in the literature as new and modern techniques must be
tested and criticized and then an improved suitable structure for the OMR is to derive
to solve the trajectory tracking problem by avoiding some famous problems like theinitial peaking phenomenon, the convergence rate and the estimation accuracy. The
proposed structure should demonstrate its reliability even in existing modeling errors,parameter uncertainties and external disturbances. The stability behavior of thecontrolled system is then analyzed.
Finally, simulations as well as experimental tests are carried out to validate theeffectiveness of the designed control system.
Mrs Eya Labidi
2020-2021: Final Class in Applied Bachelor’s Degree –IndustrialComputing, Embedded Systems,
2020 Summer internship : Office tasks in a maintenancedepartment of Data, Center Integration – NOUVAMEQ, 20172018: Maths Bachelor’s Degree, 2014-2018 : English Studies
in British Council Tunisia

6Dr. Zied Tmar, Associate Professor in Electrical Engineering,holder of a PhD in Electrical Engineering from the National
Engineering School of Tunis (ENIT), of a Master in AutomaticControl. He held several positions at Tunisian andinternational universities as Coordinator of end of studies
projects at the Higher Institute of Technological Studies in
Nabeul (1997-2003) and at the Higher Institute of Medical
Technologies in Tunis (2003-2009), and director of theElectrical Engineering department at the College ofEngineering of Jazan University in Saudi Arabia (2009-2016).
Since 2017, he has been coordinator of research and co-constructed masters in the Higher
Institute of Information Technologies and Communication (ISTIC) at the University ofCarthage. His research mainly focuses on the study of nonlinear systems, their control
and the detection and isolation of their faults via algebraic and geometric state
observation approaches.
1-3 Adaptative Control of VTOL
The work developed in this paper treat the problems of simultaneous actuator and sensor
fault estimation for an Aircraft System. The original system can often be modeled aspolytopic linear parameter varying (LPV) plants for which some estimation techniquesof fault and state still hard to solve. Here, we propose a new approach to design anadaptive observer based on quadratic Lyapunov approach. The solution is described as
an optimization problem formulated in terms of Linear Matrix Inequalities (LMI)
techniques. A simulation design shows that the new algorithm yields to reliable state
estimation and simultaneous fault detection of the LPV model of Aircraft System which
illustrate the validation of the proposed method.
Dr. Mongi Besbes
Vice President of University Carthage
DE, University Carthage
ME, University Carthage
BE, University Carthage

2-1 Discussion about an anonymous and trusted communication environment
Currently, common publication and communication environments are provided by large
private service providers, so called “platformers”. They are basically operated based oncommercial and marketing principles. In the environment, a writer is vulnerable to7unfair denial of service attacks by a group people with confronting opinions, since theopportunity for the publication is controlled by the platformer’s regulations. In this paper,
the possibilities of a trusted communication environment using blockchain technology is
discussed. We assume several distributed managers (DMs) issuing accounts of users,
which follow minimal regulation to keep anonymity and fair activities of participants.
Firstly, the double issuing of accounts from a single user is prohibited and supervised bya blockchain mechanism. Secondly, activities such as publishing, evaluations,recommendation, citation and so on are operated fairly with an allocated number ofpoints. The number of points is maintained by the blockchain mechanism as well. We
discuss the realizability and feasibility of such a system from the points of view offairness and anonymity.
Dr. Akihiro Fujii
2008-Present: Hosei University, Professor, Former Dean ofgraduate school of Science and Engineering, also honorary
research official at National Institution for Science andTechnology Policy (NISTP), Ministry of Education, Culture,
Sports, Science and Technology (MEXT), Japan
2004-2008: Senior Researcher at (NISTP, MEXT), 1999-2000:
Visiting Scholar, MIT U.S.A, 1997: Associate Professor at
Miyagi University, 1993: PhD from Tohoku Univ. Japan

2-2 Reputation Analysis Based on Weakly-Supervised Bi-LSTM-Attention Network
Due to the emergence of blowout fast food information in Web2.0 era, a large amount of
weakly labeled information (star rating, etc.) has been widespread. Weakly Supervised
Deep Embedding (WDE) model is a good choice for giving a full play of this kind of data,
the ratings are treated as the weakly-supervised signals for pre-training, fine-tune thewhole model with small amount of manually labeled data. In this research, we proposed
to change the original unidirectional transmission into bidirectional in the LSTM layer
to capture the semantics in both directions, and attention mechanism is introduced,
which is helpful to capture the important information in the context and improve theaccuracy of sentiment classification. Finally, we use TF-IDF and LDA topic model to mine
the review topics, excavate the consumers’ opinions on different sentiment polarities.
Ms. Xiang Kun
2019: Bachelor of Management in Beijing Forestry University
2017: Sessional Course in Brighton University
2021: Master of Engineering in Hosei University, majored in Applied
Informatics
Main Research Field: Natural Language Processing/ Internet of Things/
Linked Open Data/ Vision Intelligence. Committed to combine
informatics technology with other popular industries with practicalsignificance.

82-3 Practical and Interpretable Deep Learning Techniques in our Iyatomi's Lab
In this presentation, I will give an overview of the various works based on deep learningin our Iyatomi's lab, and especially introduce my research on natural language
processing (NLP). Today, deep learning is a fundamental technology that attracts a great
deal of attention and has become a keystone of Artificial Intelligence (AI). This
technology has demonstrated many outstanding achievements in a variety of tasks. In
our lab, for example, we have published various achievements in automatic plant diseasediagnosis, cancer diagnosis, content-based image retrieval from brain MRI, cybersecurity,
as well as NLP is no exception. NLP is one of a field of AI that gives the machines theability to read, understand and derive meaning from human languages, and deeplearning models have provided excellent performance in this field as well. However, themodels generally become a black box that is difficult to interpret for prediction from ahuman perspective. This presentation will introduce some techniques and models used
to interpret the model predictions I am working on, from both basic and applied research
aspects.
Mr. Shunsuke Kitada
He received his B.E. degree in science and engineering andhis M.S. degree in engineering from Hosei University,
Tokyo, Japan, in 2018 and 2020, respectively, where he iscurrently working toward his Ph.D. His research interests
include natural language processing, computer vision, andcomputational advertising. He is a Japan Society for the
Promotion of Science (JSPS) research fellow DC2 at Hosei
University. He was the recipient of the student honorable
mention from the Information Processing Society of Japan(IPSJ) in 2019 and honorable mention from the Young Researcher Association for NLP
Studies (YANS) in 2019.
Dr. Hitoshi Iyatomi
Hitoshi Iyatomi is a professor of Applied Informatics at
Hosei University, Japan. He received his B.E, M.E andPh.D (engineering) degrees from Keio University, Japan
in 1998, 2000, and 2004, respectively. During 2000-2004,
he worked for Hewlett-Packard Japan as a technicalconsultant. He joined Hosei University as a research
associate in 2004. In 2011, he earned his second Ph.D
degree (medical science) from Tokyo Women’s Medical
University. In 2016-2017, he was a visiting scholar at
Johns Hopkins University. He has authored and coauthored more than 120 peer-reviewed journal andconference papers in various research areas based onmachine learning such as computer vision, medical
applications and natural language processing.
9Dr. Jinjia Zhou
received B.E. degree from Shanghai Jiao Tong
University, China, in 2007.She received M.E. and
Ph.D. degrees from Waseda University, Japan, in2010 and 2013, respectively. From 2013 to 2016, she
was a junior researcher with Waseda University,
Japan. Currently she is an Associate Professor with
Hosei University, Tokyo, Japan.During 2017-2019,
She is also a senior visiting scholarship in State Key
Laboratory of ASIC &amp; System, Fudan University,
China. Dr. Zhou was selected as a research fellow by
the Japan Society for the Promotion of Science during 2010-2013. She is selected as JST
PRESTO researcher during 2017-2021. Her interests arein algorithms and VLSI
architectures for multimedia signal processing.

10