Would you like a flexible postgraduate degree covering Big Data, Fintech, Automation, Creative Technologies or Automated Vision?
Our M.Sc. AI is a 4 semester part-time degree which means that you can achieve it in slightly over a year. Since we are aware that some of you work, all of our lectures are held after 17:00 and are distributed over three evenings per week. The taught modules are held in the first two semesters and the thesis is concentrated in the last two semesters. Even though we offer the five streams mentioned earlier, the course is flexible enough to allow you to mix-and-match modules. E.g. you can take modules from the Big Data Stream combined with the Fintech Stream or any other combination you prefer.
We understand that sometimes, commitments are overwhelming and it would be impossible for you to pursue an MSc. Don’t despair! We are also offering our MSc modules as individual short courses. So if you’re interested in only one module out of the whole MSc, you can do just that. If you want to do two or more, you’re free to do so. When you achieve at least 6 modules (within a maximum span of 5 years), you can then enroll in our MSc and just do the thesis. Using such a model we are offering you maximum flexibility which adjusts to your personal requirements.
Furthermore, if you are carrying out a research project at work, we are also offering a Full-Time MSc AI which allows you to combine your work effort with your studies under the supervision of our lecturers and in collaboration with the organization you work for. Thus attaining the best of both words, the commercial aspect combined with scientific rigour.
Our degrees can also be sponsored via government and EU schemes. For further details, please have a look at the following https://myscholarship-apply.gov.mt
If you’re interested, please feel free to send us an email on ai@um.edu.mt
Would you like a flexible postgraduate degree covering Big Data, Fintech, Automation, Creative Technologies or Automated Vision?
Our M.Sc. AI is a 4 semester part-time degree which means that you can achieve it in slightly over a year. Since we are aware that some of you work, all of our lectures are held after 17:00 and are distributed over three evenings per week. The taught modules are held in the first two semesters and the thesis is concentrated in the last two semesters. Even though we offer the five streams mentioned earlier, the course is flexible enough to allow you to mix-and-match modules. E.g. you can take modules from the Big Data Stream combined with the Fintech Stream or any other combination you prefer.
We understand that sometimes, commitments are overwhelming and it would be impossible for you to pursue an MSc. Don’t despair! We are also offering our MSc modules as individual short courses. So if you’re interested in only one module out of the whole MSc, you can do just that. If you want to do two or more, you’re free to do so. When you achieve at least 6 modules (within a maximum span of 5 years), you can then enroll in our MSc and just do the thesis. Using such a model we are offering you maximum flexibility which adjusts to your personal requirements.
Furthermore, if you are carrying out a research project at work, we are also offering a Full-Time MSc AI which allows you to combine your work effort with your studies under the supervision of our lecturers and in collaboration with the organization you work for. Thus attaining the best of both words, the commercial aspect combined with scientific rigour.
Our degrees can also be sponsored via government and EU schemes. For further details, please have a look at the following https://myscholarship-apply.gov.mt
If you’re interested, please feel free to send us an email on ai@um.edu.mt
An always repeating presentation used at the Mozilla/Nightingale booth at LSM 2014 Montpellier. It tries to showcase most of Nightingales features by directly presenting the UI. Fully image based, as a similar presentation was alternatively running on an Android device as slideshow.
Improved Iris Verification System
Basma M.Almezgagi, M. A. Wahby Shalaby, Hesham N. Elmahdy Faculty of Computers and Information, Cairo University, Egypt.
Approach to Seismic Signal Discrimination based on Takagi-Sugeno Fuzzy Inference System
E. H. Ait Laasri, E. Akhouayri, D. Agliz, A. Atmani Electronic, Signal processing and Physical Modelling Laboratory, Physics’ Department, Faculty of Sciences, Ibn Zohr University, B.P. 8106, Agadir, Morocco
The 2011 IEEE/WIC/ACM International Conference on Web Intelligence » industry...Francois Pouilloux
The industry day of the conference aims to bring together people from both academia and industry in a venue that highlights application and practical impact.
I'm pleased to present there on August 22nd 2011.
Stay tuned for the prez file after the event !
Track 12. Educational innovation
Authors: Araceli Queiruga Dios, Angel Martin Del Rey, Ascensión Hernández, Jesus Martin-Vaquero, Luis Hernandez Encinas and Gerardo Rodriguez Sanchez
An always repeating presentation used at the Mozilla/Nightingale booth at LSM 2014 Montpellier. It tries to showcase most of Nightingales features by directly presenting the UI. Fully image based, as a similar presentation was alternatively running on an Android device as slideshow.
Improved Iris Verification System
Basma M.Almezgagi, M. A. Wahby Shalaby, Hesham N. Elmahdy Faculty of Computers and Information, Cairo University, Egypt.
Approach to Seismic Signal Discrimination based on Takagi-Sugeno Fuzzy Inference System
E. H. Ait Laasri, E. Akhouayri, D. Agliz, A. Atmani Electronic, Signal processing and Physical Modelling Laboratory, Physics’ Department, Faculty of Sciences, Ibn Zohr University, B.P. 8106, Agadir, Morocco
The 2011 IEEE/WIC/ACM International Conference on Web Intelligence » industry...Francois Pouilloux
The industry day of the conference aims to bring together people from both academia and industry in a venue that highlights application and practical impact.
I'm pleased to present there on August 22nd 2011.
Stay tuned for the prez file after the event !
Track 12. Educational innovation
Authors: Araceli Queiruga Dios, Angel Martin Del Rey, Ascensión Hernández, Jesus Martin-Vaquero, Luis Hernandez Encinas and Gerardo Rodriguez Sanchez
Scheme for motion estimation based on adaptive fuzzy neural networkTELKOMNIKA JOURNAL
Many applications of robots in collaboration with humans require the robot to follow the person autonomously. Depending on the tasks and their context, this type of tracking can be a complex problem. The paper proposes and evaluates a principle of control of autonomous robots for applications of services to people, with the capacity of prediction and adaptation for the problem of following people without the use of cameras (high level of privacy) and with a low computational cost. A robot can easily have a wide set of sensors for different variables, one of the classic sensors in a mobile robot is the distance sensor. Some of these sensors are capable of collecting a large amount of information sufficient to precisely define the positions of objects (and therefore people) around the robot, providing objective and quantitative data that can be very useful for a wide range of tasks, in particular, to perform autonomous tasks of following people. This paper uses the estimated distance from a person to a service robot to predict the behavior of a person, and thus improve performance in autonomous person following tasks. For this, we use an adaptive fuzzy neural network (AFNN) which includes a fuzzy neural network based on Takagi-Sugeno fuzzy inference, and an adaptive learning algorithm to update the membership functions and the rule base. The validity of the proposal is verified both by simulation and on a real prototype. The average RMSE of prediction over the 50 laboratory tests with different people acting as target object was 7.33.
Consumer Biometrics: Market and Technologies Trends 2018 Yole DéveloppementYole Developpement
Over the last five years the promising, highly dynamic consumer biometric sensor market has been totally reshaped.
More information here: https://www.i-micronews.com/report/product/consumer-biometrics-market-and-technologies-trends-2018.html
Soft Computing is the fusion of methodologies that were designed to model and enable
solutions to real world problems, which are not modeled or too difficult to model, mathematically. Soft
computing is a consortium of methodologies that works synergistically and provides, in one form or
another, flexible information processing capability for handling real-life ambiguous situations. Its aim is to
exploit the tolerance for imprecision, uncertainty, approximate reasoning and partial truth in order to
achieve tractability, robustness and low-cost solutions. The guiding principle is to devise methods of
computation that lead to an acceptable solution at low cost, by seeking for an approximate solution to an
imprecisely or precisely formulated problem.Soft Computing (SC) represents a significant paradigm shift
in the aims of computing, which reflects the fact that the human mind, unlike present day computers,
possesses a remarkable ability to store and process information which is pervasively imprecise, uncertain
and lacking in categoricity. At this juncture, the principal constituents of Soft Computing (SC) are: Fuzzy
Systems (FS), including Fuzzy Logic (FL); Evolutionary Computation (EC), including Genetic
Algorithms (GA); Neural Networks (NN), including Neural Computing (NC); Machine Learning (ML);
and Probabilistic Reasoning (PR). In this paper we focus on fuzzy methodologies and fuzzy systems, as
they bring basic ideas to other SC methodologies
A HYBRID ALGORITHM BASED ON INVASIVE WEED OPTIMIZATION ALGORITHM AND GREY WOL...gerogepatton
In this research, two algorithms first, considered to be one of hybrid algorithms. And it is algorithm represents invasive weed optimization. This algorithm is a random numerical algorithm and the second algorithm representing the grey wolves optimization. This algorithm is one of the algorithms of swarm intelligence in intelligent optimization. The algorithm of invasive weed optimization is inspired by nature as the weeds have colonial behavior and were introduced by Mehrabian and Lucas in 2006. Invasive weeds are a serious threat to cultivated plants because of their adaptability and are a threat to the overall planting process. The behavior of these weeds has been studied and applied in the invasive weed algorithm. The algorithm of grey wolves, which is considered as a swarm intelligence algorithm, has been used to reach the goal and reach the best solution. The algorithm was designed by SeyedaliMirijalili in 2014 and taking advantage of the intelligence of the squadrons is to avoid falling into local solutions so the new hybridization process between the previous algorithms GWO and IWO and we will symbolize the new algorithm IWOGWO. Comparing the suggested hybrid algorithm with the original algorithms it results were excellent. The optimum solution was found in most of test functions.
Secure Image Encryption using Two Dimensional Logistic Map
* Gangadhar Tiwari1, Debashis Nandi2, Abhishek Kumar3, Madhusudhan Mishra4 1, 2Department of Information Technology, NIT Durgapur (W.B.), India 3Department of Electronics and Electrical Engineering, NITAP, (A.P.), India 4Department of Electronics and Communication Engineering, NERIST, (A.P.), India
Non-Invertible Wavelet Domain Watermarking using Hash Function
*Gangadhar Tiwari1, Debashis Nandi 2, Madhusudhan Mishra3
1,2 IT Department, NIT, Durgapur-713209, West Bengal, India,
3ECE Department, NERIST, Nirjuli-791109, Arunachal Pradesh, India,
Converting UML class diagram with anti-pattern problems to verified code based on Event-B
Eman K. Elsayed
Mathematical and computer science Dep., Faculty of Science,
Al-Azhar University, Cairo, Egypt
Unit Commitment Using a Hybrid Differential Evolution with Triangular Distribution Factor for Adaptive Crossover
N. Malla Reddy* K. Ramesh Reddy** and N. V. Ramana***
Intelligent e-assessment: ontological model for personalizing assessment activities
Rafaela Blanca Silva-López1, Iris Iddaly Méndez-Gurrola1, Victor Germán Sánchez Arias2
1 Universidad Autónoma Metropolitana, Unidad Azcapotzalco.
Av. San Pablo 180, Col. Reynosa Tamaulipas, Del. Azcapotzalco, México, D.F.
2 Universidad Nacional Autónoma de México
Circuito Escolar Ciudad Universitaria, 04510 México, D.F.
Visual Perception Oriented CBIR envisaged through Fractals and Presence Score
Suhas Rautmare, Anjali Bhalchandra
A. Tata Consultancy Services, Mumbai B. Govt. College of Engineering, Aurangabad
Measuring Sub Pixel Erratic Shift in Egyptsat-1 Aliased Images: proposed method
1M.A. Fkirin, 1S.M. Badway, 2A.K. Helmy, 2S.A. Mohamed
1Department of Industrial Electronic Engineering and Control, Faculty of Electronic Engineering,
Menoufia University, Menoufia, Egypt.
2Division of Data Reception Analysis and Receiving Station Affairs, National Authority for Remote Sensing and Space Sciences, Cairo, Egypt.
The State of the Art of Video Summarization for Mobile Devices:
Review Article
Hesham Farouk *, Kamal ElDahshan**, Amr Abozeid **
* Computers and Systems Dept., Electronics Research Institute, Cairo, Egypt.
** Dept. of Mathematics, Computer Science Division,
Faculty of Science, Al-Azhar University, Cairo, Egypt.
Overwriting Grammar Model to Represent 2D Image Patterns
1Vishnu Murthy. G, 2Vakulabharanam Vijaya Kumar
1,2Anurag Group of Institutions, Hyderabad, AP,India.
Texture Classification Based on Binary Cross Diagonal Shape Descriptor Texture Matrix (BCDSDTM)
1P.Kiran Kumar Reddy, 2Vakulabharanam Vijaya Kumar, 3B.Eswar Reddy
1RGMCET, Nandyal, AP, India, 2Anurag Group of Institutions, Hyderabad, AP, India
3JNTUA College of Engineering, India.
Employing Simple Connected Pattern Array Grammar for Generation and Recognition of Connected Patterns on an Image Neighborhood
1Vishnu Murthy. G, 2V. Vijaya Kumar, 3B.V. Ramana Reddy
1,2Anurag Group of Institutions, Hyderabad, AP,India.
3Mekapati Rajamohan Reddy Institute of Technology and Science, Udayagiri, AP,India.
Bench Marking Higuchi Fractal for CBIR
A. Suhas Rautmare, B. Anjali Bhalchandra
A. Tata Consultancy Services, Mumbai B. Govt. College of Engineering, Aurangabad
1. A novel Hybrid Search for Minimal Perturbation Problems based
on Backjumping and Dynamic backtracking methods
EL GRAOUI EL MEHDI1
, BENELALLAM IMADE2
, BOUYAKHF EL
HOUSSINE1
1
LIMIARF, Department of Physics, Faculty of Sciences, Mohammed
V University, Rabat, Morocco
2
National Institute of Statistics and Applied Economic, Irfane
Rabat, Morocco
1www.icgst.com
http://www.icgst.com/paper.aspx?pid=P1121521384
2. Many real-life problems in Artificial Intelligence (AI) as well as in other areas can be
efficiently modeled and solved using constraint programming techniques. In many real-life
scenarios the problem is partially dynamic. For example, once a change appears in the
environment, after the original problem resolution, this change should be reflected in the
new solution. The minimal perturbation problem considers such changes, as well as the
initial solution to define a new problem whose solution should be as close as possible to the
initial solution. In this paper, we propose two new approaches: HS MPP backjumping and HS
MPP dynamic backtracking. These algorithms are based on HS MPP approach (Hybrid Search
for Minimal Perturbation Problem) [1]. They rely on the intelligent backtracking methods,
namely the backjumping and dynamic backtracking which allow reducing the number of
constraints tested and thus the computational time. The evaluation of performance is
applied for random binary problems and meeting scheduling problems, with the criteria of
computation time, number of constraints checks and number of visited nodes. Finally, the
empirical results with these search methods show the efficiency of our proposed
algorithms.
2www.icgst.com
http://www.icgst.com/paper.aspx?pid=P1121521384
A novel Hybrid Search for Minimal Perturbation Problems based on
Backjumping and Dynamic backtracking methods
Abstract
3. 3www.icgst.com
El Mehdi El Graoui received his M.Sc. in computer science and telecommunications
from Mohammed V University of Rabat, faculty of Science, Morocco in 2012. He is a
PhD student at LIMIARF Laboratory under the supervision of Mr. El Houssine
BOUYAKHF in Mohammed V University of Rabat. He has published papers in various
international conferences. His research interests include the satisfaction and
optimization of constraints problems and the artificial intelligence.
1
LIMIARF, Department of Physics, Faculty of Sciences, Mohammed V University,
Rabat, Morocco
http://www.um5a.ac.ma/index.php/en/
4. 4www.icgst.com
Imade BENELALLAM is currently an Assistant Professor teaching at the National Institute of Statistics and
applied Economic. He works also within the LIMIARF Laboratory Mohammed V University-Agdal. Imade
BENELALLAM received his Ph.D. degree in Computer Science from Mohammed V University-Agdal Morocco
in April 2010. He did his Ph.D. under the supervision of professor El Houssine Bouyakhf director of LIMIARF
Lab with the collaboration of professor Christian Bessiere director of research at CNRS, University
Montpellier 2, France. His Ph.D. research focused on Distributed Constraint Reasoning. The title of his thesis
is: “Exact approaches to DisCSPs and DCOPs problems’’. From 2005 to 2010 he was a computer science
engineer at Mohammed V University-Agdal Morocco. Now he is a member of the AI team. AI is a research
team that aims to propose and combine models and algorithms in constraints, learning and agents. He
works in different projects with industrial partner; the most significant was with Thales group. Imade
BENELALLAM is also the Chair of the GOLD Affinity Group of IEEE Morocco section. He was the IEEE GOLD
representative of Morocco section in various congresses.
National Institute of Statistics and Applied Economic, Irfane Rabat, Morocco
http://www.insea.ma/
5. 5www.icgst.com
El Houssine BOUYAKHF is full Professor at the Faculty of Sciences, Mohammed-V University, Rabat, teaching
Computer Sciences, Pattern Recognition, Image Processing and Artificial Intelligence. He is the scientific
leader of LIMIARF Lab (Laboratory of Informatics, Applied mathematics, Artificial Intelligence and Pattern
recognition). He received the Engineer degree from Sup'Aéro (ENSAE) National Higher School of Aeronautics
and Space, Toulouse, France; he received the Doctor Engineer degree in Pattern recognition and Artificial
Intelligence from University Paul Sabatier, Toulouse, France and “Doctorat d'Etat” in Robotics and Artificial
Intelligence from LAAS of CNRS and University Paul Sabatier, Toulouse, France. His main topics of interest
are: Artificial Intelligence and Constraint programming, Robotics and Vision, and Telecommunications. El
Houssine BOUYAKHF supervises several PhD theses in the research themes listed before and site leader or
key person of international projects. He has more than 100 scientific publications.
1
LIMIARF, Department of Physics, Faculty of Sciences, Mohammed V University,
Rabat, Morocco
http://www.um5a.ac.ma/index.php/en/