Important Dates
Submission deadline
June 25th, 2020
Notification of acceptance / rejection
Within 7-10 working days after submission
Registration deadline
One week after Notification of Acceptance
Conference Days 
October 18-19, 2020


Classification, Segmentation and Characterization of Brain Tumor in Mri Images Using Machine Learning Scheme

Dr. Norma Alias, Universiti Teknologi Malaysia

Norma Alias is an Associate Professor at Department of Mathematical Sciences, UTM Johor Malaysia and Research Fellow at Centre for Sustainable Nanomaterials, Ibnu Sina Institute for Scientific and Industrial Research, UTM Johor Bahru (CSNano). Currently, she is a Research Fellow at CSNano. She has supervised for 9 PhD students and 28 MSc students. She is supervising ongoing 5 PhD students, 12 MSc students and reviewing postgraduate students, Computing faculty, Science Faculty, Sport Science Research Center, UTM, UITM and UMS. There are 9 innovations and invention medals received, published more than 200 publications, 4 Intellectual property declarations, 2 patent disclosures, 2 product commercialization. She has completed 20 research grants and handling ongoing task as project leader and principal researcher for 28 number of research grants with more than RM 3,000,000 budget. 

Abstract: Early detection of brain tumor is crucial for diagnostic, prognosis and therapeutic management, and therefore the chances of survival of patients. Magnetic resonance imaging (MRI) is a popular tool for diagnosis nowadays because it is non-invasive, and the images produced are of multi-spectral and of high resolution. In view of this, computer aided diagnosis (CAD) is an excellent paradigm to automate the diagnosis process up to molecular level and resolve the variation of opinions among radiologists and clinical experts. Based on this motivation, this research proposes a complete pathway, including detection, segmentation and characterization of brain MRI images. Firstly, brain MRI will be identified as either normal or tumorous. Secondly, tumorous brain MRI will undergo unsupervised clustering-based image segmentation approaches to isolate brain tumor region. Thirdly, the segmented tumor region will be classified to be pituitary tumor, meningioma or glioma. The research framework in discriminating the types of tumor is similar to what is described in the first task. Some machine learning methods trained with 4 modified ICA features achieve the alternative classification. This shows the discriminative power and relevance of the extracted ICA features.


Consensus Control of Multiagent Systems

Prof. Dr. Hamid Reza Karimi, Department of Mechanical Engineering, Italy

Hamid Reza Karimi (M’06–SM’09) received the B.Sc. (First Hons.) degree in power systems from the Sharif University of Technology, Tehran, Iran, in 1998, and the M.Sc. and Ph.D. (First Hons.) degrees in control systems engineering from the University of Tehran, Tehran, in 2001 and 2005, respectively. He is currently a professor of Applied Mechanics with the Department of Mechanical Engineering, Politecnico di Milano, Milan, Italy. His current research interests include control systems and mechatronics with applications to automotive control systems, vibration systems and wind energy. 

Abstract: Recently, the problem of distributed cooperative control design has received much attention from both theoretical and practical aspects. In this context, multiagent systems has also received increasing attentions due to its advantages and abilities in coordination and enhancement of the system operation tasks including more flexibility, decentralization, stronger robustness. Some practical research impacts could be utilization of multiagent systems in intelligent manufacturing (Industry 4.0), structural control systems, emergency patient transportation, robotics, for instance. The objective of this talk is to present some challenges and recent results on consensus control, as a fundamental control problem of multiagent systems. Specifically, various design of distributed control protocol are presenetd such that a group of autonomous agents reach an agreement in some sense, which can be potentially used in many potential applications, for instance, mobile robots. The talk will be concluded with some concluding remarks on both technical and practical aspects of distributed control systems for consensus problems of multiagent systems.

Dr. Mehmet Emir Koksal, Department of Mathematics, Ondokuz Mays University, Turkey

Mehmet Emir Koksal is an Associate Professor of Mathematics at the Department of Mathematics of Ondokuz Mays University, Turkey. His major field of study is development of numerical solution methods for PDEs using finite difference, element and volume methods. He has published a number of reviewed research papers on this field. He does also research on mathematical modeling and analyzing of various engineering problems using PDEs. His another research area is the study of the investigation of commutativity of continuous and discrete time-varying linear systems. He works on the commutativity conditions of relaxed and unrelaxed linear time-varying systems, commutativity of feedback systems, decomposition of high-order systems, transitivity property of commutativity and benefits and applications of commutativity. His researches have been mainly supported by the Scientific and Technological Research Council of Turkey. On this field, he has led two national projects. He has published a number of reviewed research papers and received numerous grants and awards. He has served as a reviewer for over 50 refereed scientific journals and conferences and reviewed over 200 manuscripts. He has undertaken many administrative duties in various commission and committees of universities. Moreover, He has been a member of organizing and scientific committees of many famous international conferences.

Abstract: Most control systems are composed of successive treatments of signals by a chain of subsystems. Each subsystem performs some part of a complete process. Most of the time, it is the designers’ decision how and in what sequence the controllers are assembled with the plant when its control is of concern. The sequence of processing is important to achieve the desired aim with the maximum proficiency. The order of subsystems may be changed without affecting the overall functioning of the assembly so that an optimum sequence is achieved, but this is true if the subsystems interchanged are time invariant.  If any one of the subsystems in the chain of process is of time varying, then this is not so easy since any arbitrary change will disturb the input-output relation of the whole system so that the main functioning disappears. In this case the problem of commutativity arises; that is, under what conditions the sequence of two subsystems can be changed so that the combined performance is invariant under this change. To arrive a better system performance, the sequence of two time-varying subsystems in a control system can be changed only if these subsystems are commutative. Otherwise, the complete system spoils its main functioning and the attempt becomes unsuccessful. In this talk, a panoramic review of these contributions will be introduced, and some new subjects are suggested for future research. The topics and/or the relevant important features that will be covered are listed as follows: Concept and definition of commutativity of systems, General commutativity conditions for relaxed and unrelaxed LTVASs, Commutativity of Euler systems, Commutativity of analog feedback systems, Decompositions of second and third-order LTVASs, Transitivity property, Benefits of commutativity, Discrete time systems, Future works. 



Commutativity of Analog and Digital Systems and its Applications

Dr. Navid Bayati, Aalborg University

Navid Bayati received the B.Sc. degree in Electrical Engineering from Arak University, Arak, Iran, in 2014. Also, he received the M.Sc. degree in Electrical Engineering from Amirkabir University of Technology, Tehran, in 2017. He is currently pursuing the Ph.D. degree in Electrical Engineering (Power Systems) with the Department of Energy Technology, Aalborg University, Denmark. Since 2019, he has been involved in research with Loughborough University, UK. His research interests are power system protection, DC Microgrid, and fault detection and location of renewable energy resource-based systems. He was a recipient of Top 1% Reviewer in the world in 2019.

Abstract: DC Microgrid has become a superior power system in recent years due to development of DC loads and higher efficiency of DC systems. One of the challenging problems of DC Microgrids is protection, and it is still a particular concern associated with the challenges of developing a proper protection scheme owing to its characteristics and lack of adequate standards in DC protection. Due to the significant increasing interest on DC Microgrid; in this presentation, the DC circuit breaker structures is investigated. The differences between AC and DC circuit breakers will be presented, and the future trends on designing DC circuit breakers will introduce.


DC Microgrid Protection


The Technique of Characteristic Sets (Char Set) Established by Ritt and Wu

Dr. Farkhanda Afzal, National University of Science and Technology (NUST)

Dr. Farkhanda Afzal is a HEC approved PhD supervisor who did her PhD from Beihang University, Beijing, China. She has published numerous research papers in world reputed journals and various national, international conferences. She has been invited speaker in several countries. Dr Farkhanda remained on the faculties of Beihang University Beijing, Bahria University Islamabad, KRL College Kahuta and University of Education Lahore. At present, she is serving at Department of Humanities & Basic Sciences in MCS, NUST, Pakistan. Dr Farkhanda has been selected among 200 most qualified Young Researchers from all over world to attend Heidelberg Laureate Forum 2018, Heidelberg, Germany. She was invited speaker and organiser at 19th international conference of Pure Mathematics 2018, Islamabad.  She is member of Technical and Review committee of IPAM (ICMAE). Dr. Farkhanda is serving as editorial board member and reviewer for various reputed journals.

Abstract: The technique of characteristic sets (Char set) established by Ritt and Wu has been turned into a useful tool in order to explore systems of polynomial and differential polynomials sets and systems. With the help of char set method, we can convert any system differential polynomials into triangular form. In order to triangularize differential polynomial sets and systems, we can use char sets method. This method uses differential pseudo division for elimination of variables successively. We have proved that Differential Pseudo division can be replaced by important reductions for computing differential char sets. An algorithm is presented for computing the differential char sets efficiently. This algorithmic scheme has been executed with precise admissible differential reductions.


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