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Scientific Research
Group in Egypt
(SRGE)
Annual
Report January, 1
st
Can you imagine our life without scientific research?
Obviously, the answer is "without scientific research our
world would suffer a lot". There is no doubt that it plays an
important role in our daily life. It gives us effective means
for developing our activities in all fields of life including
health, industry, education, energy and many more. The
current achievements of science and research can be
abused as happened in the field of atomic energy but
science and research must continue to be the basic tools for
construction, development, and spreading peace for the
sake of having a better future for the mankind. This
Research Groups bring together active Egyptian
researchers and those with a professional interest in a
particular aspect of computational intelligent, intelligent
environment, network security, machine learning,
bioinformatics and biomedical and related disciplines. As
well as build and maintain close relationship with Egyptian
researchers, groups, and organizations.
Professor
Aboul Ella Hassanien
SRGE Founder and Chair
Information Technology Dept. Faculty
of Computers and Information, Cairo
University
5102
1 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
SRGE Objectives
To encourage and make it easy for the Egyptian
young researchers to cooperate and increase their
contribution in academic research.
Help investigating the usage of the
computational intelligence expertise to address
challenging real-life problems in different
branches of science.
To strengthen scientific and technological
excellence on a particular research area.
To integrate the various research efforts of the
scientific team to be a source of innovation on
possible scientific, technological and socio-
economic trajectories to mould the future of
Machine Intelligence and applications
To produce Master/PhD graduates:
- who can conduct high quality academic research,
- who can publish their research in high quality
academic journals
- who can obtain tenure track faculty positions at
high ranking research universities
- who are good teachers, and more generally
who are good academics
AISI2015 Conference – Cairo University
حداث ألهم اأ ل لألنظمة األو الدوليتنظيم المؤتمر
5102وعلوم الحاسب الذكية
: منها متنوعة عمل ورش
وتهميش الحاضر الماضياألقزام بين عظمة
حفل تكريم لألعضاء المتميزين
2 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
أهم الفعاليات خالل العام 5102
تنظيم العديد من ورش العمل في الجامعات المصرية، وإلقاء محاضرات وندوات علمية
بعدد من المدن المصرية ميدانية بحثية وخيريةطالبية وإضافة إلى أنشطة
3 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
SRGE Members
SRGE Founder and Chair
Aboul-Ella Hassanien (Abo) Email: abo@egyptscience.net Professor
SRGE Vice Chairs
Nashwa El-Bendary nashwa.elbendary@aast.edu Associated Professor
Tarek Gaber tmgaber@gmail.com Associated Professor
Ph.D. Members and Researchers
Name Email Position
Eid Emary eid.emary@yahoo.com Assistant Professor
Faculty of Computers and
Information, Cairo University
Noura A. Semary
noura.samri@ci.menofia.edu.eg Assistant Professor
Faculty of Computers and
information, Menofia University
Mohamed Mostafa Eltaweel,
mmostafa_fouad@yahoo.com
Assistant Professor
Arab Academy for Science,
Technology, and Maritime
Transport
Yasser Mahmoud Awad
ryasser@gmail.com Assistant Professor
Faculty of Agriculture,
Suez Canal University,
Mohamed Tahoun matahoun@gmail.com Assistant Professor
Faculty of Computers &
Informatics,
Suez Canal University
Amira S. Abdel-Aziz amiraabdelaziz@gmail.com Assistant Professor
Universit´e Francaise d’Egypte,
Cairo
Mahmood A. Mohamed dr_mahmoodissr@hotmail.com Assistant Professor
Institute of Statistical Studies and
Researches (ISSR) Cairo
University
Mohamed Yehia Zahab mohamed.dahab@gmail.com Assistant Professor
King Abdulaziz University
Faculty of Computing and
Information Technology
Department of Computing
Science.
Hany Soliman nhany73s@gmail.com Systems Engineering at Faculty of
Engineering, Ain Shams
4 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
SRGE Ph.D. Students
Name Email Position
Hanaa El Chazly hanosoma3002@yahoo.com Faculty of Computers and
Information, Cairo University Ossama Alshabrawy ossama_alshabrawy87@yahoo.com Dept. of Mathematics and
Computer Science, Faculty of
Science, Damietta University,
Damietta, Egypt
Reham Gharbia reham_ghrabia@yahoo.com Nuclear Materials Authority
Hossam Zawbaa hossam.zawba3a@gmail.com Faculty of Computers and
Information, BeniSuef
University
Mahir Alsharif mahiralsharif@yahoo.com Institute of Statistical Studies
and Researches (ISSR) Cairo
University
Mohamed Zaki mzissr@yahoo.com Institute of Statistical Studies
and Researches (ISSR) Cairo
University
Ahmed M. Anter sw_anter@yahoo.com Faculty of Computers and
Information, CS Department,
Mansoura University, Egypt
Alaa Tharwat engalaatharwat@hotmail.com Electrical Engineering
University
Mona Ali
mona.sedeek@mu.edu.eg
Faculty of Computers &
Informatics, Minia University
Fatma H. Ismail h. ismail_taha@informatique-
eg.com
Maryam Hazman maryam.hazman@egyptscience.net Central Laboratory for
Agricultural Expert System,
Agricultural Research Center
Heba Eid heba.fathy@yahoo.com Faculty of Science, Al Azhar
University
Ayman Taha yman.taha@gmail.com Faculty of Computers and
Information, Cairo University
Hamdi Mahmoud dr_hamdimahmoud@yahoo.com Faculty of Computers and
Information, BeniSuef University
Mona Soliman monasolyman_it@yahoo.com Faculty of Computers and
Information, Cairo University
Ahmed Hamza Asad Ah_assad@hotmail.com Institute of Statistical Studies and
Researches (ISSR) Cairo
University Abdelhameed Ibrahim
: afai79@mans.edu.eg
Assistant Professor at Faculty of Engineering, Mansoura University
5 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Department, Suez Canal
University, Fac. of Eng.
Ismailia, EGYPT
Ragia A. Ibrahim ragia11@hotmail.com Institute of Statistical Studies
and Researches (ISSR) Cairo
University Islam Amin Eng.IslamAmin@gmail.com Institute of Statistical Studies
and Researches (ISSR) Cairo
University
Ahmed Hassan ahmed.hassan@egyptscience.net Computer Science Department,
Faculty of Computer and
Information, Benha University,
Benha
Usama Mokhtar usamamokhtar@yahoo.com Institute of Statistical Studies
and Researches (ISSR) Cairo
University
Saleh Esmate salehesmate@gmail.com Faculty of Veterinary
Medicine, Cairo University
Sameh Hassanien Basha
SamehBasha@sci.cu.edu.eg Mathematics Department,
Faculty Of Science, Cairo
University.
Ashraf Hendam ashraf.hendam@egyptscience.net Institute of Statistical Studies
and Researches (ISSR) Cairo
University
Abdalla Mostafa abdalla_mosta75@yahoo.com Institute of Statistical Studies
and Researches (ISSR) Cairo
University
Kadry Ali Ezzat
Kadry_ezat@hotmail.com Biomedical Engineering
Department, Higher
Technological Institute 10th of
Ramdan city
SRGE Master Students
Name Email Position
Esraa Mohammed eng.esraa.elhariri@gmail.com Faculty of Computers and
Information, Fayoum
University, Fayoum - Egypt Hend Hussein serry ali hend.serry.issr@gmail.com Institute of Statistical Studies
and Researches (ISSR) Cairo
University
Walaa H. Elmasry walaa.elmasry@gmail.com Faculty of Computers and
Information, Cairo University
Gehad Hassan gehad_hassan_cs@yahoo.com Faculty of Computers and
Information, Fayoum
University
6 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Ahmed Hamdy h01.ahmed@gmail.com Faculty of Computers and
Information, Cairo University
Ahmed Zaki Abdelwahb awimam@yahoo.com Faculty of Computers and
Information, Cairo University
Ahmed Ibrahem Hafez ah.hafez@gmail.com Faculty of Computer and
Information, Minia University,
Minia – Egypt
Heba Mohamed Ayeldeen heba.ayeldeen@gmail.com Faculty of Computers and
Information, Cairo University
Shaimaa Ahmed shima.ahmed89@hotmail.com Faculty of Computers and
Information, Cairo University
Moetaz Kilany moetaz.kilany@egyptscience.net Faculty of Computers and
Information, Minia University
Moustafa Zein moustafazn@gmail.com Computer Science
Department, Thebes Academy
-Cairo - Egypt
Eslam Ali Hassan eslam.ali@fci-cu.edu.eg Faculty of Computers and
Information, Cairo University
Rania Elesawy elesawyrania@gmail.com Institute of Statistical Studies
and Researches (ISSR) Cairo
University
Waleed Yamany waleed_2math@yahoo.com Faculty of Computers and
Information, Fayoum
University
Moustafa Mahmoud Faculty of Computers and
Information, Minia University
Asmaa Sweidan asmaa.sweidan@yahoo.com
Faculty of Computers and
Information, Fayoum
University, Fayoum - Egypt
Mai Salem maisalem90@gmail.com Faculty of Computers and
Information, Cairo University
Asmaa Hashem Abd El-
tawab
asmaa.sweidan@yahoo.com Faculty of Computers and
Information, Fayoum
University, Fayoum - Egypt
Ehab Hamdy ehabhamdy2012@gmail.com Faculty of Computers and
Information, Minia University
Moetaz Kilany moetaz.kilany@gmail.com Faculty of Computers and
Information, Minia University
Rehab mahmoud eng.rehabmahmoud@gmail.com
Faculty of Computers and
Information, Fayoum
University, Fayoum - Egypt
Mona Abbass mona_abbass12@hotmail.com
Central Laboratory for
Agricultural Expert System,
Agricultural Research Center
Gehad Ismail darkspot_1993@yahoo.com Faculty of Computers and
7 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Information, Cairo University
Undergraduate Students
Name Email Position
Hassan Aboul Ella
Hassanien
hasanabo94@gmail.com Faculty of Veterinary Medicine,
Cairo University
Pre-doctor SRGE Students
Name Email Position
Rasha Wahid Abd Elreheem rashawahid@ymail.com Al-Azhar University, Faculty of
Science, Cairo,
Abdalla Mostafa Abdalla abdalla_mosta75@yahoo.com Institute of Statistical Studies and
Researches Cairo University
Sara Abdelghafar abdelghafarsara@yahoo.com Al-Azhar University, Faculty of
Science, Cairo,
Mourad Raafat mouradraafat@yahoo.com Mathematics Department, Faculty
of Science, Helwan university
Abder-Rahman Ali abder-rahman.a.ali@ieee.org Scientific Research Group in
Egypt
Mohamed Abdelfata m_abdelfatah@ymail.com Scientific Research Group in
Egypt
Local Collaborative Researchers
Name Email Position
Samar Kassim samar_kassim@yahoo.com Ain Shams University -
Faculty of Medicine Mohamed Fahmy Tolba fahmytolba@gmail.com Ain Shams University, Faculty
of Computers and Information
Aly Aly Fahmy aly.fahmy@gmail.com Faculty of Computers and
Information, Cairo University
Hoda M.Onsi drhoda2002a@hotmail.com Faculty of Computers and
Information, Cairo University
Sanaa El Ola sana.ola@fci-cu.edu.eg Faculty of Computers and
Information, Cairo University
Hesham Hefny hehefny@hotmail.com Institute of Statistical Studies
and Researches (ISSR) Cairo
University
Abeer El_korany abeer_el_korany@hotmail.com Faculty of Computers and
Information, Cairo University
Mohamed Elsayed
Ghoneim
m_ghoniem02@yahoo.co.uk Mathematics department,
Faculty of Science, Damietta
University, Egypt
Ahmed Taher ahmad_t_azar@ieee.org Faculty of Computers and
Information, Benha University,
Egypt
8 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Mohamed Abu ElSou mohamed_hossieny@yahoo.com Faculty of Computers and
Information, CS Department,
Mansoura University, Egypt
Ashraf khodier a.khodeir@yahoo.com Faculty of Science, Ain Shams
University
Ali Ismail Awad aawad@ieee.org Faculty of Engineering
Al Azhar University, Qena,
Egypt
International Collaborative Researchers
Name Email Position
Ajith Abraham ajith.abraham@ieee.org Machine Intelligence Research
Labs, USA
Dominik Selzak Dominik.Slezak@infobright.com Warsaw Institute of
Technology, Poland
Emilio Corchado escorchado@ubu.es University of Burgos, Spain
James Peters jfpeters@ee.umanitoba.ca Department of Electrical and
Computer Engineering University
of Manitoba
Jan Platos an.platos@vsb.cz VSB-Technical University of
Ostrava, Czech Republic
Kazumi Nakamatsu nakamatu@shse.u-hyogo.ac.jp University of Hyogo , Hyogo,
Japan
Robert C. Berwick berwick@csail.mit.edu Massachusetts Institute of
Technology (MIT)
Soumya Banerjee
dr.soumya@ieee.org Birla Institute of Technology,
India
Milos Kuaelka milos.kudelka@inflex.cz VSB-Technical University of
Ostrava, Czech Republic
Václav Snášel vaclav.snasel@vsb.cz VSB-Technical University of
Ostrava, Czech Republic
Tai-Hoon Kim taihoonn@empal.com
Kai Xiao Shawkey@gmail.com Shanghai Jiao Tong University,
China
Qiangfu Zhao qf-zhao@u-aizu.ac.jp Aizu Tong University, Japan
Qing Tan qingt@athabascau.ca Athabasca University, Canada
Soumya Banerjee dr.soumya@ieee.org Department of Computer
Science, Birla Institute of
Technology, Mesra, India
Manash Sarkar manashsarkar53@gmail.com Department of Computer
Science, Birla Institute of
Technology, Mesra, India
Eiman Tamah Al-
Shammari
eiman.tamah@gmail.com Kuwait Univ., Faculty of
Computing Science and Eng. Adel M. Alimi adel.alimi@ieee.org REGIM-Lab., University of
9 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Sfax, BP 1173, Sfax, Tunisia Ning Zhang
nzhang@cs.man.ac.uk School of Computer Science
Universtiy of Manchester
Manchester, UK Micael Couceiro micaelcouceiro@isr.uc.pt
Institute of Systems and Robotics,
Polo II, Pinhal de Marrocos,
University of Coimbra, Portugal Nilanjan Dey neelanjan.dey@gmail.com Bengal College Engineering and
Technology, India
Amr Ahmed aahmed@lincoln.ac.uk The University of Lincoln, UK
10 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
SRGE Tracks and Directions
Direction-I: Intelligent Technology for Disabled People
Direction-II Intelligent Environment and Applications
Direction III Computational Intelligence and Optimization
Direction-IV: Network and Information Security
Direction-V: Bio-informatics and Bio-medical Engineering
Direction-VI: Social networks and graph mining
Direction VII: Animal Identification
Direction VIIII: Cheminformatics
11 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Direction-I: Intelligent technology for
elderly and disabled people
Direction Chair
Direction Objective
Elderly and disabled people compose a segment of the population that would profit very
much from Ambient Intelligence if it is accessible. This is only possible if accessibility
barriers are early detected in the evolution of the Ambient Intelligence. Disability is
generally seen as a curse and people with disabilities are often considered as a burden
on their families and communities. All this can change when these people are offered a
chance to demonstrate their talents. The Intelligent technology for Disabled People
subgroup at theSRGE focuses on the recent technology including the computer vision,
speech processing, e-learning, image processing and object recognition in complex
domains. The challenge of this group is to address these technologies in the broader
context of Artificial Intelligence, and to integrate techniques from empirical evaluation
and machine learning. Group goal is to use these techniques to develop computer vision
systems whose behaviors are both reliable and understood. Research points are:
- Text to speech processing
- Document management for blind and visual impairment
- Developing Games for blind and visual impairment
- Mobil applications for blind and visual impairment
- Automatic Sign Language (ASL) Recognition for Deaf-Blind
people
- Intelligent Mobile Interaction: A Learning System for Mentally
Disabled People - Smart Home Applications for disabled
- Smart Home Applications for disabled - Prediction and Analysis of Seizure Propagation
12 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Direction-II: Intelligent environment and
applications
Direction Chair
Direction Objective
Intelligent environment is any space where ubiquitous
technology informs the learning process in an unobtrusive, social
or collaborative manner. Thus an intelligent environment can be
an aware room or building, capable of understanding something
about the context of its inhabitants or workers. The objective and
mission of the Intelligent Environment group is to use the
technologies of computational intelligence and wireless sensor
networks in order to solve some environmental-related problems;
such as water and air pollution monitoring and alerting, as well
as develop different smart environments that are automatically
adjustable depending on users’ preferences. On the other hand,
adding a wireless dimension to biometric identification systems
(BIS) provides a more efficient and reliable method of identity
management across criminal justice and civil markets. The
research topics that are currently being carried out by the IE
group are:
- Smart Reading Environments (Intelligent Classroom)
Intelligent Lighting system
- Intelligent Water/Air Quality Monitoring
- Biometrics over communication
- Structural Health Monitoring (SHM)
- Intelligent Environment for Tele-education
- Intelligent Health monitoring
- Intelligent Wireless Sensor Networks
- Intelligent traffic monitoring in vehicular WSN\
- Mobile Biometrics identification
13 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Direction III Computational intelligence and
optimization
Direction Chair
Direction Objective
Computational Intelligence (CI) is the study of adaptive
techniques to enable or facilitate intelligent behavior in complex
and changing environments. These techniques are covered:
artificial neural networks, and some meta-heuristics techniques
like evolutionary computing (genetic algorithm (GA), genetic
programming (GP), differential evolution (DE), and scatter
search (SS), swarm intelligence (particle swarm optimization
(PSO), ant colony (AC), fish swarm optimization...), immune
system and fuzzy systems. Computational intelligence
techniques have been applied to solve many real word problems.
Most of these problems can be represented as an optimization
problem. Optimization is an important tool in decision science
and in the analysis of physical systems. In order to apply CI
techniques as an optimization technique, we must first identify
some objective, a quantitative measure of the performance of the
system under study (objective function). This objective could be
profit, time, potential energy ... Our goal is to find values of the
variables that optimize the objective. Often the variables are
restricted, or constrained, in some way. For instance, quantities
such as electron density in a molecule and the interest rate on a
loan cannot be negative.The research topics cover the following
applications:
- Protein 3D structure prediction
- Image processing (image fusion, image segmentation,...)
- Solving large scale global optimization problems
- Multi-objective optimization
- Data mining tasks (Classification, clustering...)
14 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Direction-IV: Network and Information
Security
Direction Chair
Direction Aim
Different information technologies have enabled substantial growth in the
field of global economic. However, this makes these technologies rich
targets for criminal activity. Also, the reliance on electronic devices by
nearly all societies is exponentially increasing and holding valuable
information on personal computers or performing critical operations
through networks become very important for personals and companies. To
support these issues, network and information security are very crucial in
the current digital era. The Network and Information Security (NIS) group
aims to bring security concept and applications to the information society
whereas preserving persons’ rights, particularly the privacy of the persons.
NIS group focuses on application scenarios (e.g. secure electronic
commerce, implicit authentication, security of Wireless Sensor Network
(WSN), and digital content distribution), while investigating and
addressing different technical challenges in different areas, such as
cryptology, personal identification and biometrics, computer trust, security
awareness, access control and authentication, watermarking,
steganography and steganalysis, anonymity, unlinkability, information
hiding, privacy. Currently, members of NIS group are conducting research
in the following areas:
Digital Right Management
Implicit authentication
Access Control
Security Issues in Social Networks.
Security of WSN
Image authentication
Cryptanalysis
Biometrics including face, fingerprint, and iris print
Watermarking
Anonymity
Privacy
15 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Direction-V: Bioinformatics and biomedical
engineering
Direction Chair
Direction Interests
The last few years have witnessed significant developments in
various aspects of Biomedical Informatics, including Bioinformatics,
Medical Informatics, and Biomedical Imaging. The explosion of
medical and biological data requires an associated increase in the
scale and sophistication of the automated systems and intelligent
tools to enable the researchers to take full advantage of the available
databases. This ranges from the effective storage of data and their
associated data models, to the design of efficient algorithms to
automate the data mining procedures, and also to the development of
advanced software systems to support data integration. With more
researchers taking on Bioinformatics projects that integrate
theoretical and applied concepts from both Bioscience as well as
Computational Sciences. The massive size of the current available
biological and medical databases and its high rate of growth want to
be focusing more than ever to maximize the use of these
databases.The Biomedical informatics group mission is to design
computer-based decision aids and develops decision support systems
for clinical decision making and scientific discovery using
computational intelligence and image processing technologies.
Currently, members of BI group are conducting research in the
following areas:
Bioinformatics
Medical image processing
Breast cancer analysis, (sonar, MRI, fMRI, CT)
Liver fibrosis and tumor analysis (biopsy, MRI, CT)
3D Dental image processing and visualization
16 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Direction-VI: Social Networks and Graph
Mining
Direction Chair
Social Networks encourage the cross-disciplinary research integration of different
sciences such as computer science, engineering, biology, physics, anthropology, social
sciences, etc.. The main goal of this track is to improvise cross-disciplinary research
discussions that are of relevance to new and novel computer networking ideas,
applications and experimental results in the area of all forms of social networks in thre
form of Ph.D and MS quality projects. The research topics that are currently being
carried (2012-2013) out by the Social Informatics and Graph Mining group are:
Social networks analysis
Social information retrieval
The impact of social networking on future
Network Design
System design for Social Networks
Evolutionary Social science of Networks
Knowledge discovery from large Social
Networks
17 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Direction VII: Animal Identification
Direction Chair
Tradition animal identification methods such as ear notching or even the
electrical identification methods like RFID are not able to provide
accurate and secure animal identification due to theft, fraudulent and
duplication. Adopting human biometric traits into animals is a
promising technology for animal identification domain, and overcomes
some of the traditional techniques limitations. In addition, it has many
applications such as animal classification, cattle tracking from birth to
the end of food chain, and understanding the animal diseases' trajectory
and population. Accordingly, some animal biometrics traits such as iris
patterns, vascular patterns and muzzle prints have been investigating for
animal identification. As a result, the biometrics-based animal
identification faces almost the same challenges of human identification
systems in terms of the system's response time and the identification
accuracy. These challenges need to be addressed in order to enhance the
biometrics system's performance. The research directions in The
Scientific Research Group in Egypt (SRGE) cover the information
security topics, and focus on animal identification as an interesting
branch of information security. The vision of the SRGE tries to couple
the Information Technology (IT) techniques with real time problems.
Addressing such problems will be beneficial for the individual
researchers, the society, and it can be diverse to overall the world.
18 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Direction VIII: Cheminformatics
Direction Chair
The study of the role of the chemical compounds in the biological
systems has been further strengthened. The correlation between the
characteristics of the chemical compounds and its activity is utilized in
the prediction of the activity of any chemical compound. Chemists
provided a set of properties for different compounds named as
descriptors of these compounds. Each compound is characterized by a
set of Structural, Physiochemical, Topological and Geometrical
Descriptors. Toxicity is an activity of chemical compounds that has the
capacity of a substance to produce injury or illness. Toxicity testing
aims to evaluate what harm may be caused by exposure to chemicals,
including medicines, industrial and consumer products, and food
additives, to humans and the environment. Animal-based testing
causes millions of animals to suffer unalleviated pain and death has
questionable value for predicting human health effects.
Cheminformatics or Chemical informatics is the application of
information technology to help chemists to reduce the numbers of
chemical experiments by the prediction of the toxicity of the
compounds.
19 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
SRGE Members
Professor Aboul Ella Hassanien
Qualifications: Aboul Ella Hassanien (Abo) received his B.Sc.
with honors in 1986 and M.Sc degree in 1993, both from Ain
Shams University, Faculty of Science, Pure Mathematics and
Computer Science Department, Cairo, Egypt. On September 1998,
he received his doctoral degree from the Department of Computer
Science, Graduate School of Science & Engineering, Tokyo
Institute of Technology, Japan.
Function::Dr Aboul Ella Hassanein is the Founder and Head of the
Egyptian Scientific Research Group (SRGE) and a Professor of
Information Technology at the Faculty of Computer and
Information, Cairo University. Professor Hassanien has more than
500 scientific research papers published in prestigious
international journals and over 30 books covering such diverse topics as data mining, medical images,
intelligent systems, social networks and smart environment. Research works and publications: Prof.
Hassanien is a collaborative researcher member of the Computational Intelligence Laboratory at the
Department of Electrical and Computer Engineering, University of Manitoba. He also holds the Chair of
Computer Science and Information Technology at the Egyptian Syndicate of Scientific Professions (ESSP).
Dr Hassanien is the founder and head of Africa Scholars Association in Information and Communication
Technology. His other research areas include computational intelligence, medical image analysis, security,
animal identification and multimedia data mining. Awards and prizes: Prof. Hassanien won several awards
including the Best Researcher of the Youth Award of Astronomy and Geophysics of the National Research
Institute, Academy of Scientific Research (Egypt, 1990). He was also granted a scientific excellence award
in humanities from the University of Kuwait for the 2004 Award, and received the superiority of scientific -
University Award (Cairo University, 2013). Also He honored in Egypt as the best reseracher in Cairo
Univesrity in 2013. He was also received the Islamic Educational, Scientific and Cultural Organization
(ISESCO) prize on Technology (2014) and received the state Award (جائزة الدولة)for excellence in engineering
sciences 2015. Community service:: Dr Hassanien’s great many activities in community and the
environment service include organizing 40 workshops hosted by a large number of universities in almost all
governorates of Egypt. He has been honored by a number of university presidents and governors for his
active engagement in community service. His other community service activities include promoting
awareness about the importance of ICT in promoting the lives and status of people, with particular focus on
the disabled, children of the internet and the homeless. Chief among these were the Egyptian disabled
celebrations, held on the theme “Partners in one world without barriers”, in addition to a workshop on
Smartphone’s techniques and their role in the development of visually impaired skills in various walks of life,
a conference on the role of communications and social networking technology in fostering integration of
persons with special needs amid present challenges, a workshop on protecting children from internet
hazards and several training workshops at various Egyptian universities.
20 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Intelligent Environments (IE): Trends
and Applications Nashwa El-Bendary, Associated Professor
Arab Academy for Science, Technology, and Maritime Transport, Cairo, Egypt
Chair of Intelligent Environments (IE) Track- Scientific Research Group in Egypt (SRGE)
Email: nashwa.elbendary@ieee.org, nashwa.elbendary@aast.edu
Abstract: Intelligent Environments (IEs) are spaces in which networked computing technologies are
seamlessly embedded to enhance people’s ordinary daily activities via creating interactive environments that
are sensitive and responsive to the presence of people. Various places people inhabit encompassing settings
such as homes, classrooms, factories, transport, clothing, etc., provide various types of IEs. Moreover, IEs
describe physical environments in which information and communication technologies and sensor systems
disappear as they become embedded into physical objects, infrastructures, and the surroundings in which we
live, travel, and work. Therefore, the main goal of developing IE applications is to allow computers to take
part in activities never previously involved and allow people to interact with computers via gesture, voice,
movement, and context. On the other hand, Intelligent Environments (IEs) can be considered as
environments with installed low cost intelligent sensor-network based monitoring systems to effectively
monitor environmental changes; such as variations in the conditions, patterns, and dynamics of air, water,
and land resources as well as enabling collecting and processing environmental data into information that
can be used for management and planning as well as prediction and recovery.
Nashwa El-Bendary: She received her Ph.D. degree in 2008 in Information
Technology from the Faculty of Computers and Information, Cairo University, Egypt.
She is an assistant professor at the Arab Academy for Science, Technology, and
Maritime Transport, Egypt. She is the chair of the Intelligent Environments (IE) track
of the Scientific Research Group in Egypt (SRGE). In the year 2013, she was a visiting
lecturer in University Teknologi Malaysia (UTM), KL, Malaysia, and then she was a
post-doctoral fellow in School of Computing and Information Systems, Athabasca University, Alberta,
Canada. Dr. Nashwa El-Bendary has published several papers in major international journals and peer-
reviewed international conference proceedings along with a number of book chapters. Her main research
interests are in the areas of Ambient Intelligence and Intelligent Environments, Ubiquitous Smart Systems,
Smart Environmental Monitoring, Mobile Computing and Technologies, Wireless Sensor Networks,
Machine Learning, and Image Processing. She currently co-advises master and Ph.D. students as well as
leading and supervising various graduation projects. Dr. Nashwa is a member of the editorial boards of a
number of international journals. She has also been a reviewer, technical program committee member,
special sessions/workshops co-chair, and has been invited as a speaker to several workshops and
international conferences.
Nashwa El-Bendary, Esraa El Hariri, Aboul Ella Hassanien, Amr Badr: Using machine learning
techniques for evaluating tomato ripeness. Expert Syst. Appl. 42(4): 1892-1905 (2015)
21 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Thermal Imaging: Opportunities and Challenges for Breast
Cancer Detections
Name: Tarek Gaber Ph.D. in Computer Sciences (Information Security) Faculty of Computers & Informatics, Suez Canal University, Ismailia 41522, Egypt
Member of Scientific Research Group in Egypt (SRGE) (www.egyptscience.net) Email: tmgaber@gmail.com
Abstract. : Breast cancer is the most common cancer among women in the world. It is estimated that one
in eight women, all over the wide, would develop breast cancer during her life. The breast cancer is
considered one of the first-leading causes of cancer deaths among women. The early detection of breast
cancer could save many women's life. Mammogram is one of the most imaging technology used for
diagnosing breast cancer. Although mammogram has recorded a high detection and classification
accuracy, it is difficult in imaging dense breast tissues, its performance is poor in younger women, it is
harmful, and it could not detect breast tumor that less than 2 mm. To overcome these limitations, it was
found that there is a relation between the temperature and the presence of the breast cancer. Utilizing this
fact, infrared thermography could be a good source of breast images to study and detect the cancer at the
early stages which is crucial for cancer patients for increasing the rete of the breast cancer survival.
Tarek Gaber received a PhD degree from the University of Manchester in
Computer Science in 2012. He has worked as an Assistant Lecturer at many
universities including Faculty of Computers and Information Sciences, Ain
Shams University, and the School of Computer Science, University of
Manchester, Manchester, UK. Currently, he is an Assistant Professor at the
Faculty of Computers and Informatics, Suez Canal University, Ismailia, Egypt,
and a Postdoctoral Fellow at Faculty of Electrical Engineering and Computer
Science, VSB Technical University of Ostrava, Czech Republic. Dr. Tarek has 30
publications at international conferences, journals, and book chapters. He is
currently supervising five MSc students.
Research Interest Image processing, pattern recognition, information security, machine learning, wireless
sensor network, and biometric authentication and identification
List of publications:
1- Tarek Gaber; Zahran, Gehad; Anter Ahmed; Mona Soliman; Ali Mona Abdelbaset Sadek, Semary,
Noura ; Aboul Alla, Hassanien ; Vaclav, Snasel: Thermogram Breast Cancer Detection Approach
based on Neutrosophic Sets and Fuzzy C-Means Algorithm, In the proceedings of the 37th Annual
International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC2015),
IEEE, Milano, Italy, 25-29 August, 2015.
2- Tarek Gaber, Alaa Tharwat, Abdelhameed Ibrahim, Vaclav Snasel, Aboul Ella Hassanie, Human
Thermal Face Recognition Based on Random linear Oracle (RLO) Ensembles, In the proceedings of
7th INTERNATIONAL CONFERENCE ON INTELLIGENT NETWORKING AND
COLLABORATIVE SYSTEMS (INCoS-2015) , IEEE, Taipei, Taiwan, 2-4 Sept. 2015.
22 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Colorization Method based on HSV Color Model for
Thermal Breast Cancer Enhancement
Noura Abd El-Moez Semary Assistant Professor (Ph.D.)
Scientific Research group in Egypt (www.egyptscience.net) Faculty of Computers and Information
Menofia University– EGYPT (32511)
Email: noura.semary@egyptscience.net
Fax: +204822223694
Abstract. Medical imaging is one of the most attractive topics of image processing and understanding research fields
due to the similarity between the captured body organs colors. Thermography is proven to be a good tool for detecting
breast cancer in early stages than that of mammography. Thermal camera can produce grayscale images. However, such
images are not appropriate for human interpretation but it is proven that a human (thermologists) can only discriminate
between a few dozen of gray level values where as they are able to distinguish thousands of colors. Thus, it is important
to provide the thermologists with breast thermal image such that they can find abnormal regions in these color images.
Pseudo-coloring of thermogram is one of the important methods achieving this aim (discriminating between the region
of interest (ROI) and the background (BG) parts). Most literature efforts suggested RGB-base color palettes. In this
paper, a thermal coloring method was proposed based on pseudo-coloring and it was compared with different coloring
methods. The proposed colorization method employs HSV color model to generate the desirable color scale. The
experiments have been performed on PROENG thermal images and the results show that the proposed methodology
could clearly discriminate between different temperature regions specially tumor regions.
Noura A. Semary works as an associated prof. in Faculty of Computers and Information,
Menofia University, Egypt. She has BSc in 2001 from Cairo University, Faculty of
Computers and Information. Worked as staff member in the Faculty of Computers and
Information, Menofia University, Egypt in 2003. In 2007 and 2011 she has obtained her
Master and Ph.D. degrees respectively in Information Technology from Computers and
Information Faculty at Menofia University. In 2009 she won the first rank in “Made in
Egypt” and “Made in Arab World” competitions for her project “Black and White
Movies Colorizer”. In 2012 she has joined The Scientific Research Group in Egypt
(SRGE). She has 25 publications in international conferences and journals. Also, she has
reviewed more than 10 papers for international conferences and journals in 2014. She is
also leading and supervising various graduation projects and post-graduate students.
Research Interest 1)Image Processing, 2) Computer Vision, 3) Data Compression, 4) Data Hiding,
5)Virtual Reality and 6) Assistive Technology.
Selected 2015 Publications
[1] Tarek Gaber, Gehad Zahran, Ahmed Anter, Soliman Mona, Mona Abdelbaset Sadek Ali, Noura Semary,
Hassanien Aboul Alla, Snasel Vaclav. Thermogram breast cancer detection approach based on Neutrosophic
sets and fuzzy c-means algorithm. 37th Annual International Conference of the IEEE Engineering in Medicine
and Biology Society (EMBC’15), Milano, Italy August 25-29, 2015
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7319334
[2] Faten Khalifa; Noura Semary; Hatem El-Sayed & Mohiy Hadhoud. Tarek Gaber; Aboul Ella Hassanien;
Nashwa El-Bendary (Eds.) Markerless Tracking for Augmented Reality Using Different Classifiers. The 1st
International Conference on Advanced Intelligent System and Informatics (AISI2015), November 28-30,
2015, Beni Suef, Egypt, Springer International Publishing, 2016, 407, 25-35
http://link.springer.com/chapter/10.1007%2F978-3-319-26690-9_3#page-1
23 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
The Field of Cheminformatic: Orphan Drug Legislation
System and Theoretical Similarity Searching strategy
Ammar Adl (Assistant Professor) Faculty of Computers and information
Bani-Suef University
Scientific Research Group in Egypt (SRGE)
Cairo – Egypt
E-mail: ammaradl@gmail.com
Abstract: Machine learning(ML) methodologies were applied in the past decade through hundreds of
researches to enrich Cheminformatics with high performance automatic prediction machines. The objective
of this article is to present the very recent researches of ML in the field of Cheminformatics, and to review
the history of each research through highlighting the earlier trials. We aim at introducing that review for
other researchers as an index for different trials and comparisons of ML techniques in Cheminformatics. We
present an approach to predict the activity of analogues of 2, 4, 6-trisubstituted 1, 3, 5-triazines as
cannabinoid receptor (CB2) agonists by using machine learning techniques. We compute twenty molecular
descriptors for a data set of 58 analogues for the component, and depending on the values of these
descriptors, we train random forest to find a relation between biological activity and molecular structure of
analogues. The orphan drug is a treatment for rare diseases that leads to the importance of orphan drug
development and discovery. To approve any orphan drug from the FDA, it is needed not to be similar to any
approved orphan drug, so the chemist’s opinion is the important to determine the probability of similarity. It
is too hard to check all orphan drugs for rare disease. It takes a long time and big efforts, so we introduce in
our research a system that classifies the orphan drugs based on their probability of structure similarity, and
compare between them and unauthorized orphan drugs, to determine the closest orphan drug to it. The
applications of QSAR are used to establish the correlation between structure and biological response. QSAR
represents the core of lead optimization in Drug Discovery. We introduce a theoretical similarity searching
strategy based on membrane computing in QSAR stages.
Ammar Adl received his Ph.D. degree in 2013 in Computer Science from the
Faculty of Computers and Information, Cairo University, Egypt. He is a member,
and chair of the Reality Mining track, in the Scientific Research Group in Egypt
(SRGE). His main research interests are in the areas of Mobility, Augmented
Reality, Reality Mining, Internet of Things, Telepresence, Game Design and
Architecture, Synthetic Biology, Bio-Inspired Computing, Cellular Automata,
Cybernetics and Robotics, Designing Cybernetic Organisms, Self-replicating
Machines, and Parapsychological Artificial Intelligence.
List of publications in 2015:
Ammar Adl, Moustafa Zein, Aboul Ella Hassanien: PQSAR: The membrane quantitative structure-activity
relationships in cheminformatics. Expert Syst. Appl. 54: 219-227 (2016)
24 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Meta-heuristics techniques and
applications
Ahmed Fouad Ali, (Assistant Professor)
Scientific Research Group in Egypt (Member)
Faculty of Computer and Information, Suez Canal University
Email: ahmed_fouad@ci.suez.edu.eg
Abstract: Metaheuristics are a branch of optimization in computer science and applied mathematics that are
related to algorithms and computational complexity theory. The past 20 years have witnessed the
development of numerous metaheuristics in various communities that sit at the intersection of several fields,
including artificial intelligence,computational intelligence, soft computing, mathematical programming, and
operations research. Most of the metaheuristics mimic natural metaphors to solve complex optimization
problems (e.g., evolution of species, annealing process, ant colony, particle swarm, immune system, bee
colony, and wasp swarm). My research focussing on applying the meta-heuristics techniques like (Genetic
algorithm, Tabu search, Simulated annealing, Particle swarm optimization...) to solve large scale
optimization problems, minimizing molecular potential energy function, image processing, etc.
Dr. Ahmed Fouad Ali. Received the B.Sc., M.Sc. and Ph.D. degrees in computer
science from the Assiut University in 1998, 2006 and 2011, respectively. Currently, he
is a Postdoctoral Fellow at Thompson Rivers University, Kamloops, BC
Canada. In addition, he is an Assistant Professor at the Faculty of Computers and
Informatics, Suez Canal University, Ismailia, Egypt. He served as a member of
computer science department Council from 2014-2015.
He worked as director of digital library unit at Suez Canal University; he is a member in SRGE (Scientific
Research Group in Egypt). He also served as a technical program committee member and reviewer in
worldwide conferences. Dr. Ali research has been focused on meta-heuristics and their applications, global
optimization, machine learning, data mining, web mining, bioinformatics and parallel programming. He has
published many papers in international journals and conferences
Selected Publication 2015:
Ahmed Fouad Ali, Aboul Ella Hassanien: A Simplex Nelder Mead Genetic
Algorithm for Minimizing Molecular Potential Energy Function. Applications of Intelligent Optimization in Biology and Medicine 2016: 1-21
25 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Energy-aware Sink Node Localization Algorithm for
Wireless Sensor Networks
Mohamed Mostafa Fouad, (Assistant Professor) Member of Scientific Research Group in Egypt (SRGE)
Arab Academy for Science, Technology, and Maritime Transport (AASTMT) Email: mmostafa_fouad@yahoo.com
Abstract: The road surface conditions information are very useful for the safety of road users and to inform
road administrators for conducting appropriate maintenance. Roughness features of road surface; such as
speed bumps and potholes, have bad effects on road users and their vehicles. Usually speed bumps are used
to slow motor-vehicle traffic in specific areas in order to increase safety conditions. On the other hand
driving over speed bumps at high speeds could cause accidents or be the reason for spinal injury. Therefore
informing road users of the speed bumps’ position through their journey on the road especially at night or
when lighting is poor would be a valuable feature. Therefore we exploited a mobile sensor computing
framework to monitor and assess road surface conditions. The framework is currently measured the changes
in the gravity orientation through a gyroscope and the shifts in the accelerometer’s indications, both as an
assessment for the existence of speed bumps.
Dr. Mohamed Mostafa received his M.Sc. degree in 2005 and Ph.D. degree in March
2012, both in Computer Science from the Faculty of Computers and Information,
Helwan University, Egypt. Currently, he is an assistant professor at the Business
Information System department, faculty of Management and Technology, at the Arab
Academy for Science, Technology, and Maritime Transport (AASTMT), Cairo, Egypt.
His main research interests are in the areas of Wireless Sensor Networks, Body Sensor
Networks, Intelligent Health Monitoring, Security, Machine Learning and Software
Engineering. He has published several papers in major international journals, book
chapters, and peer-reviewed international conference proceedings. In addition, he
currently advises a number of master students in addition to leading and supervising
various graduation projects. Dr. Mohamed is a member of theScientific Research Group in Egypt (SRGE). Moreover,
he is an IEEE member and a reviewer, technical program committee member, local arrangement committee member,
and special sessions' co-chair.
Research interest: Wireless Sensor Networks, Information Security and Machine Learning
Selected publications:
Mohamed Mostafa Fouad, Václav Snášel and Aboul Ella Hassanien Energy-aware Sink
Node Localization Algorithm for Wireless Sensor Networks, Int. Journal of Distributed
Sensor Networks, Volume 2015 (2015), Article ID 810356, 7 pages
http://www.hindawi.com/journals/ijdsn/2015/810356/
Mohamed Mostafa Fouad, Ahmed Ibrahem Hafez, Aboul Ella Hassanien, Vaclav Snasel
Grey Wolves Optimizer-based Localization Approach in WSNs, 11th IEEE
International Computer Engineering Conference, Cairo, EGYPT December 29-30, pp.
256 – 260, 2015
26 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Mathematical optimization in intelligent
systems
E. Emary
Scientific Research Group in Egypt (Member)
Faculty of Computer and Information, Cairo University
Email: e.emary@fci-cu.edu.eg
Abstract: Optimization is defined as the search for a combination of parameters commonly referred to as
decision variableswhich minimize or maximize some ordinal quantity; fitness. Intelligent systems always
help in decision making or makes decisions itself based on either formulating human experience or learning
from past examples. To reach acceptable performance in intelligent system quick and optimal training or
learning methods should depend on optimization to reach the training or learning goal(s). Intelligent systems
can be employed in many application areas such as medical image analysis in 2D or 3D, signal processing,
sensor networks, …
E. Emary, was born in Sharkia, Egypt in 1979. He received his B.Sc. degree in 2001 and
M.Sc. degree in 2003, from Faculty of Computers and Information, Information
Technology Dept., Cairo University, Egypt. Currently, he is a Lecturer at Information
Technology Dept., Faculty of Computers and Information, Cairo University, Egypt. He
has authored/co-authored over 15 research publications in peer-reviewed reputed journals,
book chapters and conference proceedings.He has served as the technical program
committee member of various international conferences and reviewer for various
international journals. His research interests are in the areas of computer vision, pattern recognition, video
and image processing, machine learning, data mining, and biometrics.
Selected publication:
1. Aboul Ella Hassanien, Eid Alamry, Swarm Intelligence: Principles, Advances, and
Applications, CRC – Taylor & Francis Group, 2015, ISBN 9781498741064 - CAT# K26721
2. Aboul Ella Hassanien, Eid Emary, Hossam M. Zawbaa: Retinal blood vessel localization
approach based on bee colony swarm optimization, fuzzy c-means and pattern search. J. Visual
Communication and Image Representation 31: 186-196 (2015)
27 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Environmental Management and Intelligent
Environment: Climate Change and Pollution Impacts
on Agriculture and Possible Mitigation Technologies
Yasser Mahmoud Awad, (Assistant Professor)
Ph.D. in Environmental Sciences (Plant Ecology)
Member of Scientific Research Group in Egypt (SRGE)
Faculty of Agriculture, Suez Canal University, Ismailia 41522, Egypt
E-mail: ryasser@gmail.com
Abstract: Environmental degradation is due to the depletion of natural resources, including air, water and
soil by mainly unsustainable human practices and activities. Specifically, intensification of agriculture and
anthropogenic activities threaten seriously the state of agroecosystem, reducing soil and water quality, as
well as crop production and food safety. Recently, climate change has pronounced impacts on agriculture in
Egypt as indicated by a low productivity of some crops according to the weather problem. Elevated CO2 and
temperature can alter not only photosynthetic enzyme activities, fruit ripeness and crop-water requirement,
but also the spreading of plant diseases due to the increase in humidity via high plant density or sporulation
of pathogens. Therefore, there is a necessity to develop novel technologies as innovative solutions to the
aforementioned problems because Egypt could experience increased pressures on food security.
Yasser M. Awad, is a lecturer at the Department of Agricultural Botany, Faculty of Agriculture,
Suez Canal University (SCU), Egypt. He received his B.Sc. (soil and water sciences) and M.Sc.
(agricultural botany), Faculty of Agriculture, SCU in 1997 and 2004, respectively. He received
his Ph.D. in environmental sciences (plant ecology), Department of Biological Environment,
College of Agriculture and Life Sciences, Kangwon National University (KNU), 200-701
Chuncheon, South Korea, 2012. His Ph.D. was conducted as a part of Doctoral Student
Exchange Program between KNU in Chuncheon, Korea and University of Bayreuth (UBT), in
Bayreuth, Germany through a joint Education and International Research Training Project
funded by DFG/KOSEF(project title: Complex TERRain and ECOlogical Heterogeneity
"TERRECO"). He also served as a researcher in several international projects (2009-2012)
dealing with agroecosystem management and safety assessment of toxic metals and antibiotics
in the agricultural environment (soil and water). He has published 16 papers in international
journals and conferences.
Research Interest Research interests: 1) Best management practices to mitigate climate change and environmental
pollution (technologies for reduction of soil erosion and maintenance of soil/water quality), 2)
Diagnosis and quantification of plant responses to environmental stress using WSNs and expert
systems (drought, and crop-diseases using the thermal imaging), 3) Phytoremediation, and 4)
Organic farming and sustainable agriculture (intelligent aquaponic system and greenhouse).
Selected References
Awad, Y.M., Abdullah, A.A., Bayoumi, T.Y., Abd-Elsalam, K., Hassanien, A.E. (2015). Early Detection of
Powdery Mildew Disease in Wheat (Triticum aestivum L.) Using Thermal Imaging Technique. The Institute
of Electrical and Electronics Engineers (IEEE) Intelligent Systems IS’14 Conference: Theory and
Applications, pp. 755-765, 24–26 September 2014, Warsaw, Poland.
Abdel Salam, M., Mahmood, M.A., Awad, Y.M., Maryam Hazman, Nashwa El Bendary, Hassanien, A.E.,
Tolba, M., Vaclav Snasel and Saleh, S.M. (2014).Climate recommender system for wheat cultivation in
North Egyptian Sinai Peninsula. In Proceedings of the Fifth International Conference on Innovations in Bio-
Inspired Computing and Applications IBICA 2014, Advances in Intelligent Systems and Computing Volume
303, pp. 121-130, Springer International Publishing, 23–25 June, Ostrava, Czech Republic.
28 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Automatic Fruit Image Recognition System
Maryam Hazman
Ph.D. Computer Sciences (Web Mining)
Member in Scientific Research Group in Egypt (SRGE) Central Laboratory for Agricultural Expert System, Agricultural Research Center E-mail: Maryam.hazman@gmail.com
Abstract: The aim of this paper is to develop an effective classification approach based on Scale Invariant
Feature Transform (SIFT) and Random Forest (RF) algorithms. Three fruits; i.e., apples, Strawberry, and
oranges were analysed and several features were extracted based on the fruits' shape, colour characteristics
as well as Scale Invariant Feature Transform (SIFT). A pre-processing phase using image processing to
prepare the fruit images dataset to reduce their color index is presented. The fruit image features is then
extracted. Finally, the fruit classification process is adopted using random forests (RF), which is a recently
developed machine learning algorithm. A regular digital camera was used to acquire the images, and all
manipulations were performed in a MATLAB environment. Experiments were tested and evaluated using a
series of experiments with 178 fruit images. It shows that RF based algorithm provides better accuracy
compared to the other well know machine learning techniques such as K-Nearest Neighborhood (K-NN) and
Support Vector Machine (SVM) algorithms. Moreover, the system is capable of automatically recognize the
fruit name with a high degree of accuracy.
Maryam Hazman is a Researcher at Central Lab for Agricultural Experts Systems,
Ministry of Agriculture and Land Reclamation. She received her Master Degree
from Cairo University with Thesis Title “Automatic Knowledge Acquisition Tool
for Scheduling Systems”. Also, she received her Ph.D Degree in Computer
Sciences & Information from Cairo University with Thesis Title “Knowledge
Discovery from the Web”. She has published 19 papers in international conferences
and journals.
Research
interest 1) Text and data mining, 2) Knowledge Engineering, 3)Knowledge Based System,
4) Information Management, and 5) Image Processing.
Selected Publication:
29 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Artificial Immune Systems for
Network Intrusion Detection and
Classification
Amira Sayed Abdel-Aziz, (Ph.D.Student)
Scientific Research Group in Egypt (Member)
Assisting professor in UniversitéFrançaised’Egypte (UFE).
Email:amiraabdelaziz@gmail.com
Abstract: With the expanding and increasing use of networks and accumulating number of internet users,
network throughput has become massive and threats are more diverse and sophisticated. Network and
information security are of high importance, and research is continuous in these fields to keep up with the
increasing complexity of attacks. Intrusion Detection is a major research area that aims to identify suspicious
activities in a monitored system, from authorized and unauthorized users, by monitoring and analysing the
system activities. Using machine learning techniques in a hybrid system gives the benefit of dealing with
complex attacks, and implementing the system as a multi-agent system gives the benefit of having a
distributed protection system for the network. Wireless networks and cloud systems are a ripe field to
investigate the design and implementation of a Network Intrusion Detection System inspired by biological
immunity as a light-weight, dynamic, and efficient system for identifying attackers and different threats to
the environment.
Amira is a Ph.D. student in Cairo University, Faculty of Computers and Information –
Information Technology department. Amira received her B.Sc. in 2000 and M.Sc.
degree in 2008, from Faculty of Computers and Information – Information Technology
department, Cairo University. Amira also obtained a Software Development Skills
diploma in 2001 from Information Technology Institute, Cairo - Egypt. She works
currently as an assisting teacher/lecturer in Faculty of Business Administration and
Information Systems, in the French university in Egypt – UniversitéFrançaised’Egypte.
Her master topic was “Network Security Using Network Intrusion Detection Systems”
where an NIDS was implemented using Multivariate statistical analysis techniques
(Hotelling’s& MEWMA) for network security. Her current research for Ph.D. is in Multi-Agent Artificial
Immune Systems, for network security as well. Her research interests include Network Security, specifically
Network Intrusion Detection, Machine Learning, Computational Intelligence, Artificial Immune Systems,
Multi-Agent systems, and Data Mining.
30 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Forecasting based on Chaotic Systems
Mohamed Yehia Zahab Assistant Professor
King Abdulaziz University
Faculty of Computing and Information Technology
Member of Scientific Research Group in Egypt (SRGE)
E-mail:Mohamed.dahab@gmail.com, MDahab@kau.edu.sa
Abstract: Accurate forecasting for future events constitutes a fascinating challenge for theoretical and for
applied researches. Foreign Exchange market (FOREX) is selected in this research to represent an example
of financial systems with a complex behavior. Forecasting a financial time series can be a very hard task due
to the inherent uncertainty nature of these systems. It seems very difficult to tell whether a series is
stochastic or deterministic chaotic or some combination of these states. More generally, the extent to which a
non-linear deterministic process retains its properties when corrupted by noise is also unclear. The noise can
affect a system in different ways even though the equations of the system remain deterministic. Since a
single reliable statistical test for chaoticity is not available, combining multiple tests is a crucial aspect,
especially when one is dealing with limited and noisy data sets like in economic and financial time series. In
this research, we propose an improved model for forecasting exchange rates based on chaos theory that
involves phase space reconstruction from the observed time series and the use of support vector regression
(SVR) for forecasting. Given the exchange rates of a currency pair as scalar observations, observed time
series is first analyzed to verify the existence of underlying nonlinear dynamics governing its evolution over
time.
Mohamed Y.Zahab, was born in Cairo, Egypt in 1965. He received his B.Sc. degree in
1987, M.Sc. degree in 2000, from Institute of Statistical Studies and Research (ISSR),
Computer Science Department, Cairo University, Egypt and Ph.D degree in 2007, from
Faculty of Computers and Information,Computer Science Department, Cairo University,
Egypt. He is a researcher Central Laboratory forAgricultural Expert Systems, Egypt.
Currently, he hasdelegatedin King Abdulaziz University, Faculty of Computing and
Information Technology, Department of Computing Science as Assistant Professor.
He has authored/co-authored over 11 research publications in peer-reviewed journals
and international conference proceedings.
Research Interest 1) Computer Vision, 2) Pattern Recognition,3) Image Processing, 4) Machine
Learning, 5) Text mining, 6) Natural Language Processing, 7) Information
Retrieval 8) Chaotic Systems.
Selected Publication:
Fawaz H.H. Mahyoub, Muazzam A. Siddiqui, Mohamed Y. Dahab, Building an Arabic
Sentiment Lexicon Using Semi-supervised Learning, Journal of King Saud University -
Computer and Information Sciences, Available online 28 September 2014, ISSN 1319-
1578, http://dx.doi.org/10.1016/j.jksuci.2014.06.003.
31 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Thermal Imaging: Challenges for Breast Cancer
Detections
Mona Abdelbaset Sadek Ali
PhD Computer Science (Sensor and Social Network)
Member of Scientific Research Group in Egypt (SRGE) Faculty of Computers and Information, Minia University Email: mony_4it@yahoo.com, mona.sedeek@mu.edu.eg
Breast cancer is the most shared cancer among women in the world. It is estimated that one in eight
women, all over the wide, would develop breast cancer during her life. The breast
cancer is ranked as one of the first-leading causes of cancer deaths among women.
The early detection of breast cancer might save women's life. Although
Mammogram is difficult in imaging dense breast tissues, its performance is poor in
younger women, it is harmful, and it could not detect breast tumor that less than 2
mm. it is still one of the most imaging technology used for diagnosing breast
cancer. To overcome these limitations, it has been found that there is extrusive
relation between the temperature and the presence of the breast cancer. Employing this fact, infrared
imaging could be a good source of breast images to study and detect the cancer at the early stages which
is crucial for cancer patients for increasing the rete of the breast cancer survival. As a result an overview
about thermal imaging technology has been studied focusing on its ability and challenges in detecting
breast cancer. Mona is a lecturer at Faculty of Computers and Information, Minia University, Egypt. She gets her B.Sc.
from Faculty of Computers and Information, Cairo University, Information Technology Department 2002.
At 2005 she gets her M.Sc from the same faculty. She gets her Ph.D from School of computers and
Informatics, Cardiff University, UK from 2008-2013. She also works as assistant lecturer at the same school
during studying time.
Publications:
Tarek Gaber; Zahran, Gehad; Anter Ahmed; Mona Soliman; Ali Mona Abdelbaset
Sadek, Semary, Noura ; Aboul Alla, Hassanien ; Vaclav, Snasel: Thermogram Breast
Cancer Detection Approach based on Neutrosophic Sets and Fuzzy C-Means Algorithm, In
the proceedings of the 37th Annual International Conference of the IEEE Engineering in
Medicine and Biology Society (EMBC2015), IEEE, Milano, Italy, 25-29 August, 2015.
32 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Digital Watermarking and and Intelligent
Optimization
Mona M. Soliman Assistant Professor
Member of Scientific Research Group in Egypt (SRGE) http://www.egyptscience.net/ Faculty of Computers and Information, Cairo University, Egypt
Email: mona.soluman@egyptscience.ne, mona.solyman@fci-cu.edu.eg
Abstract: The basic principle of watermarking approaches is to add copyright information into a
multimedia object, with the aim of broadcast monitoring, access control, copyright
protection etc. The object may be 2D image, 3D image, video or audio. Two
important and conflicting requirements in watermarking system are perceptual
transparency and robustness. Our recent research aims to develop a watermarking
system using Bio-Inspired optimization techniques. Although there are many
proposed approaches of watermark insertion and extraction either in spatial or
frequency domain, but most of these methods had a limitation of enhancing either
robustness or invisibility. The main objective of or research is devolving a
watermarking system that considers wa termarking problem as an optimization
problem. This work propose a watermarking system by utilizing the use of Bio-Inspired techniques such as
neural network, Genetic algorithm, and swarm intelligent in optimizing watermarking approaches for both
2D images and 3D images. Digital watermarking of 3D objects remains a challenging problem. The state of
research of watermarking 3D models is still in its infancy as compared to published work in image and video
watermarking. There still exist few watermarking methods for 3D meshes, in contrast with the relative
maturity of the theory and practices of image, audio and video watermarking. This situation is mainly caused
by the difficulties encountered while handling the arbitrary topology and irregular sampling of 3D meshes,
and the complexity of possible attacks on watermarked meshes. Our new research direction focus on using
intelligent systems in improving agriculture environment.
Research Interest: Image processing, Pattern recognition, Machine learning, Information
security, Image steganography, optimization methods
Selected publications:
Mona M. Soliman, Aboul Ella Hassanien and Hoda M. Onsi, An Adaptive Watermarking Approach
based on Swarm Optimization, Neural Computing and Applications Journal (IF=1.7), doi:
10.1007/s00521-015-1868-1, 2015.
33 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Towards an Optimized Registration Framework for
Remote Sensing Applications
Mohamed Tahoun Assistant Professor at Faculty of Computers and Informatics,
Suez Canal University, 41522 Ismailia, Egypt
Emails: tahoun@ci.suez.edu.eg, tahoun@egyptscience.net
Abstract. The rapid increasing of remote sensing data in many applications ignites a spark of
interest in the process of satellite image matching and registration. These data are collected
through remote sensors then processed and interpreted by means of image processing algorithms.
The detection and matching of features from satellite images taken from same or different
sensors, viewpoints, or at different times are mandatory tasks in manipulating remote sensing data
for applications like change detection and land use. The current work and recent trends in this
interesting area of research, focuses on -but not limited to-: Automatic or adaptive feature
extraction, feature descriptors and matching, geometrical transformation, optical and radar image
registration, multi-sensor image fusion, and quality assessment of image registration.
Mohamed Tahoun is an Assistant Professor at computer science department, FCI, suez
canal university. He finished his PhD thesis as a channel program between Humboldt
university in Berlin and Suez Canal university in Egypt since3. His Ph.D was about
"Matching and Registration of Satellite Images from Different Sensors”. He got his
M.Sc. degree in computer science from computer science department, faculty of
computers and information sciences, Ain Shams university, Egypt. He is working as
an assistant lecturer at computer science department, faculty of computers and
informatics, Ismailia, Egypt. He is a SRGE member since 2010 and has participated
in few international conferences and workshops in additions to some cultural and
scientific events in Egypt, Germany and Poland.
Research Interests 1) Satellite Image Registration,
2) Remote Sensing and Applications,
3) Content-Based Image Retrieval.
4) Computer Vision and Image Processing Applications.
Publications 2015
Mohamed Tahoun, Aboul Ella Hassanien, Ralf Reulke, Registration of Optical and Radar Satellite
Images Using Local Features and Non-Rigid Geometric Transformations", in Lecture Notes in
Geoinformation and Cartography Series, Springer, pp. 249-261, 2015.
34 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Image Processing and Applications
Name: Abdelhameed Ibrahim Ph.D. in Computer Engineering (Computer Vision and Pattern recognition) Faculty of Engineering, Mansoura University, Mansoura, Egypt Member of Scientific Research Group in Egypt (SRGE) (www.egyptscience.net) Email: afai79@mans.edu.eg, afai79@yahoo.com
Abstract. During the last few years, the importance of spectral imagery has sharply increased following the
development of new optical devices and the introduction of new applications. The spectral imaging system is a
system which captures and describes color information by a greater number of sensors than an RGB device
resulting in a color representation that uses more than three parameters. The problem with conventional color
imaging systems is that they have some limitations, namely, dependence on the illuminant and characteristics
of the imaging system. On the other hand, spectral imaging systems can provide spectral reflectance
information and the systems are illuminant independent. Therefore, spectral imaging must be the technique of
the immediate future. Spectral imaging is used, for example, in remote sensing, computer vision, and industrial
applications. The main advantage of spectral images, compared with color images, is the large amount of
information involved, which dramatically improves the ability to detect individual materials or separate areas
with visually different spectral bands. The disadvantage of spectral images is that, since we have to process
additional data, the required computation time and memory increase significantly. However, since the speed of
the hardware will increase and the costs for memory will decrease in the future, it can be expected that spectral
images will become more important in many fields of image analysis and computer vision. Image Processing
is one of the fields that have shown a stable growth in the last decades. It has different impact in computer
engineering and computer science and other research areas, e.g. biology, remote sensing, and medicine. Image
processing is very important in medical applications, robotics, and other industrial applications.
Abdelhameed Ibrahim was born in Mansoura city, Egypt, in 1979. He attended the
Faculty of Engineering, Mansoura University, in Mansoura, where he received Bachelor
and Master Degrees in Engineering from the electronics (Computer Engineering and
Systems) department in 2001 and 2005, respectively. He was with the Faculty of
Engineering, Mansoura University, from 2001 through 2007. In April 2007, he joined
the Graduate School of Advanced Integration Science, Faculty of Engineering, Chiba
University, Japan, as a doctor student. He received Ph.D. Degree in Engineering in 2011.
His research interests are in the fields of computer vision and pattern recognition, with
special interest in material classification based on reflectance information.
Research
Interest
My current work involves research and development of biometric authentication
methods using ear and finger knuckle images based on machine learning methods. I am
also involved in research and development of novel algorithms and techniques for fragile
watermarking for image authentication with tamper detection and localization.
Encryption is combined with the developed schemes in order to improve the tamper
detection and localization accuracy through enhancing the scheme fragility and to
provide an additional level of security. I have also worked on bladder cancer diagnosis
using artificial neural network, 3D object reconstruction and recognition, Iris based
verification techniques through fusion at matching score level, computation offloading in
mobile cloud computing, and wireless multimedia sensor networks. List of publications:
1. Tarek Gaber, Alaa Tharwat, Abdelhameed Ibrahim, Vaclav Snasel, Aboul Ella Hassanien Human Thermal Face
Recognition Based on Random Linear Oracle (RLO) Ensembles, 2015 IEEE International Conference on
Intelligent Networking and Collaborative Systems, 2-4 September 2015, Taipei, Taiwan pp. 91-98, 2015.
2. Alaa Tharwat, Abdelhameed Ibrahim, Aboul Ella Hassanien, Gerald Schaefer: Ear Recognition Using Block-
Based Principal Component Analysis and Decision Fusion. 6th International Conference Pattern Recognition and
Machine Intelligence - PReMI 2015, Warsaw, Poland, June 30 - July 3, 2015, pp,246-254
35 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Ph.D.
Students
36 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Computational Intelligence Modeling of Pharmaceutical
Processes
Hossam M. Zawbaa (Ph.D. Student) Member of Scientific Research Group in Egypt (SRGE)
Lecturer, Faculty of Computers and Information, Beni-Suef University, Beni-Suef, 61222, Egypt
Assistant Researcher, Faculty of Mathematics and Computer Science, Babes-Bolyai University,
Romania. E-mail: hossam.zawbaa@gmail.com
Abstract: Today's technology offers many ways and opportunities to advance in multi-disciplinary
fields. In the pharmaceutical industry, the exploitation of knowledge on the casual relationship
between product quality and attributes of formulations is very useful in developing new
formulations and products, and optimizing manufacturing processes. With the big data captured in
the pharmaceutical product development practice, computational intelligence (CI) models and bio-
inspired optimization algorithms, could potentially be used to identify critical quality attributes
(CQA) and critical process parameters (CPP) for the formulations and manufacturing processes.
That needs a deep investigation of the powder mixing, roller compaction, milling, and die
compaction of pharmaceutical formulations.
Hossam M. Zawbaa, was born in Cairo, Egypt in 1987. He received
his B.Sc. degree in 2008 and M.Sc. degree in 2012, from Faculty of
Computers and Information, Information Technology Department,
Cairo University, Egypt. He is a Lecturer at Information Technology
Department, Faculty of Computers and Information, Beni-Suef
University, Egypt. Currently, he has become the early stage researcher
(ESR) No. 10 in Marie Curie, IPROCOM project at Babes-Bolyai
University, Romania. He has authored/co-authored over 29 research
publications in peer-reviewed reputed journals and international
conference proceedings. He has served as the technical program
committee member of various international conferences and reviewer
for various international journals.
Research Interest 1)Computer Vision, 2) Pattern Recognition, 3) Image Processing,
4) Machine Learning, 5) Intelligent optimization, 6) Data Mining.
Selected Publication:
E. Emary, Hossam M. Zawbaa, Aboul Ella Hassanien, "Binary Grey Wolf Optimization
Approaches for Feature Selection", International Journal of Neurocomputing, Elsevier, Vol.
172, pp. 371-381 Journal indexed in 'Journal Citation Reports' (Thomson Reuters), Impact
Factor (2014): 2.083, June 2015.
37 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Mining and Visualizing the DNA
Methylation Data
Islam Amin
M.Sc. Information Systems (Bioinformatics)
Institute of Statistical Studies and Researches,
Cairo University, Egypt.
H +2 (0114) 109 7403
B Eng.IslamAmin@gmail.com
www.egyptscience.net
Abstract: DNA methylation is an epigenetic mechanism that cells use to control gene expression.
DNA methylation has become one of the hottest topics in cancer research, especially for
abnormally hypermethylated tumor suppressor genes or hypomethylaed oncogenes research. The
analysis of DNA methylation data determines the differential hypermethlated or hypomethylated
genes that are candidate to be cancer biomarkers. Visualization the DNA methylation status may
lead to discover new relationships between hypomethylated and hypermethylated genes.
Islam I. Amin is a PhD candidate student in Institute of Statistical Studies and
Researches (ISSR), Cairo Univeristy. He started his master project in Oct. 2011 and
defended it on July 2014, His master studies has focussed on mining and visualizing
DNA methylation data for determining the status of DNA methylation markers.
Islam received his BSc degree from Agriculture Sciences from Zagazig University in
2003. In May 2009, Islam was awarded the Diploma of High Studies in Information
Systems from ISSR, Cairo University. In addition to being a member of Scientific
Research Group in Egypt (SRGE), he is also a member of the Egyptian Center of
Bioinformatics and Genomics (ECBAG) He has extensive experience of bioinformatics, by combining the
knowledge of biology and molecular cell with the latter experiences of computer science theories to analysis,
model, visualize, solve the complex biological problems in plant, animal and human.
Area of Interest
Bioinformatics Microarray, Gene expression, DNA Methylation, Haplotype Analysis, Sequence Alignment,
Protein Structure, SNPs, NGS , Data Mining Supervised learning, Unsupervised learning, Modeling and
Visualizing.Statistics and Biostatistics - Probabilities, Distributions, Statistical hypothesis testing(parametric
and nonparametric tests), ANOVA, ANCOVA, Experimental Design, Regression, Correlation,
Significance And Multiple testing (FWER and FDR)..etc.
Selected Publication 2015
38 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Knowledge Discovery in Bioinformatics
Hanaa Ismail Elshazly, (Ph.D. Student)
Scientific Research Group in Egypt (Member)
Computer Science Dept., Faculty of Computers and Information, Cairo University
Email: hanosoma3002@yahoo.com
Abstract Advancement of hardware and software technology have their impact in improving investigations
in biomedical research. The increase of storage capacity and data availability encourage the collection of
data. Data can include redundant features that seem to be useful. Thus, large collected size of medical data
are expected due to the technology advancement occurred. Data dimensionality may hinder the promising
benefits of any automatic diagnostic approach. Feature selection has an improving impact over the
knowledge discovery process of medical data sets. An efficient feature selection algorithm has an intrinsic
need for a successful classification process. Dimensionality reduction realizes some advantages related to the
decrease of complexity, the visualizing information and the improvement of the comprehensibility of the
induced concepts. Rules dimensionality also have positive long term benefits related to the physician as to
accurately classify patients as well as to render the reduced rules in understandable manner. Recent studies
pointed out toward meta-heuristics techniques, as Genetic Algorithm, to perform rules reduction due to their
fast processing and promising results.
Hanaa is a Ph.D. student at Cairo University, CS Department. Hanaa received his
M.Sc degree in 2008 from Cairo University, Institute of Statistical Studies and
Research, Cairo, Egypt. Her Master topic was "Toward a Knowledge Modeling
Approach in Risk Analysis Domain". She is currently an IT manager in an Insurance
Co. Hanaa is a research member of Scientific Research Group in Egypt (SRGE). She
has worked in the areas of Modeling in Biomedicine. Her Ph.D project is in the area
of Data Mining and Visualization. Her research interests include: Soft computing,
Data mining, Machine learning and Hybrid Intelligent Systems.
Publications in 2015
39 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Remote Sensing Image Fusion
Reham Abd El Wahab Gharbia Ph.D. Student
Member of Scientific Research Group in Egypt (SRGE)
Lecturer Assistant in the Nuclear Materials Authority (NMA).
Email:reham_ghrabia@yahoo.com
Abstract: Remote sensing has many applications including military surveillance, agriculture, hydrology,
geology and meteorology among others. Image fusion is a useful technique for producing a high-resolution
multispectral image from the merging of a high resolution panchromatic image with a low resolution
multispectral image. Despite the fact that the number and kind of satellite imagery are daily increasing,
using fusion techniques, in a proper way, to eliminate the redundancy in data and increasing the quality of
them is an important challenge in Remote Sensing applications.
Reham Abd El Wahab Gharbia, is Lecturer Assistant in the Nuclear
Materials Authority (NMA). She is a PhD student at Faculty of Science,
Domyatta University. She received her B.Sc. from Faculty of Science,
Menoufiya University. She received the M.Sc. Degree in computer
science from the Faculty of Science, Menoufiya University in 2008. Her
Master topic was Mathematical Studies and Modeling of Remote
Sensing Data for Geological Investigation of Owinat Area, South
Western Desert. Her PhD project is about: Remote Sensing Data Fusion
in South Western Sinai under the supervision of: Prof. Aboul Ella
Hassanien. Her research interests include: Computer Vision, Image
Processing, and Remote Sensing.
Research Interest 1) Computer Vision 2) Image Processing 3) Remote Sensing.
4) Big Data. 5) Data Mining.
List of Publication:
- Reham Gharbia, Ali Hassan El Baz, Aboul Ella Hassanien and Vaclav Snasel. Region-based Image
Fusion Approach of Panchromatic and Multi-spectral Images, Proceedings of the Second Euro-
China Conference on Intelligent Data Analysis and Applications, ECC 2015, pp. 535-545, June 29 -
July 1, 2015, Ostrava, Czech Republic, 2015.
- Reham Gharbia, Sara A. Ahmed and Aboul Ella Hassanien. Remote Sensing Image Registration
Based On Particle Swarm Optimization and Mutual Information. Second International Conference
on INformation systems Design and Intelligent Applications 2015. January 8-9, Springer India,
2015. Pp. 399-408.
40 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Retinal blood vessel segmentation based
on ant colony system
Ahmed Hamza Asad(Ph.D. student)
Scientific Research Group in Egypt (Member)
Email: ahmed.assad1@gmail.com
Abstract: The diabetic retinopathy disease usually leads to retina revascularization by spreading diabetes on
the retina vessels and thus they lose blood supply that causes blindness in short time, so early diagnosis of
diabetes prevents blindness in more than 50% of cases. The early diagnosis depends mainly on the
segmentation of blood vessels in the retinal images. The retinal blood vessels segmentation is a classification
problem where each pixel in the field of view of retinal image is classified as vessel-like (foreground) or
non-vessel (background). The manual segmentation of retinal blood vessels is a long and tedious task which
also requires training and skill. So in the last two decades, the process of retinal blood vessels segmentation
attracts a lot of research in the medical image processing area for automating this process since it is the
critical component of any computer-aided diagnosis system of retinopathies such as hypertension, glaucoma,
obesity and etc. Among many approaches were used for segmenting the retinal blood vessels, too few were
based on a bio-inspired algorithm with other algorithm but no approach was based a bio-inspired algorithm
standalone. Biologically inspired computing is a field of study that loosely knits together subfields related to
the topics of connectionism, social behavior and emergence. It is often closely related to the field of artificial
intelligence, as many of its pursuits can be linked to machine learning. Biologically-inspired algorithms such
as genetic algorithms, particle swarm optimization, ant colony algorithms, bee colony, invasive weed
optimization, fish swarm and bat swarm have achieved some remarkable successes.
Ahmed Hamza Asad, received the B.Sc. degree in information technology from
information technology department, faculty of computers and information, Cairo
university, Egypt in 2000, and the M.Sc. degree in the same field from the same
faculty in 2008. His master topic was real-time face tracking. He is currently
working toward PhD degree at department of computer sciences and information,
institute of statistical studies and researches, Cairo University, Egypt. During
2000-2001, he worked as software developer at Sakhr Company and during 2003-
2004; he worked as software developer at Pixel Company. During 2001-2007, he
worked as teaching assistant at department of computer sciences and information,
institute of statistical studies and researches, Cairo University, Egypt. From 2008 up to now, he is working
as lecturer assistant at the same department and institute. His research interests include medical image
analysis and computer vision.
41 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Automatic Computer Aided Diagnosis System for
Abnormalities in Abdominal CT Liver Images
Ahmed MetwalliAnter, (Ph.D. student)
Scientific Research Group in Egypt (Member)
Faculty of Computer and Information, Mansoura University, Egypt.
Email: sw_anter@yahoo.com
Abstract: Liver cancer is a serious disease and is the third commonest cancer followed by stomach and lung
cancer. The most effective way to reduce deaths due to liver cancer is to detect and diagnosis in the early
stages. One of the most common and robust imaging techniques for the diagnosis liver cancer is Computed
Tomography (CT). Computer Aided Diagnosis (CAD) plays a key role in the early detection and diagnosis
of liver cancer. CAD has been proposed to improve diagnostic accuracy and to support clinical decision
making to provide the type of tumours and assist doctors to take decision, reduce cancer missed due to
fatigue, and reduce number of required biopsies. The objective of this research is the development of
automated CAD system to detect liver tumours and diagnosis based on Neutrosophic sets and meta-
heuristics bio-inspired and evolutionary algorithms.
Ahmed M. Anter, Lecturer Assistant at Faculty of Computer Science and Informatics,
Benisuef University, Egypt. Anter is interested in Biomedical Engineering, Image Processing,
Neural Network, programming and application development, Business Process Management
Systems (BPMS), Patient Information and Medical application systems, and Open Source
Technologies. Anter is a member in the scientific research group in Egypt (SRGE). He is worked
in Faculty of informatics, Jazan university as lecturer assistant, and he worked in CITC Mansoura
university as a Senior software development. Anter holds his master degree of Computer Science
from faculty of informatics, Mansoura University, 2010. His master was in “Content-Based Mammogram Image
Retrieval”. Now he is a Ph.D. student at the same faculty and working in “Automatic Computer Aided Diagnosis
System for tumours in CT Liver Images”. His research interests are in Biomedical engineering, Artificial intelligence,
Image processing, Computer vision, Data mining, Pattern recognition, Machine learning, and meta-heuristics and
optimization fields. He has published six papers in international journals and conferences and submitted three book
chapters in 2015.
Selected Publication:
- Ahmed M. Anter, Abul Ella Hassenian, Mohamed Abu ElSoud, Ahmed Taher Azar, “Automatic Liver
Parenchyma Segmentation System from Abdominal CT Scans using Hybrid Techniques”, Int.J. of Biomedical
Engineer Journal and Technology (IJBET), InderScience, Vol. 17, No. 2, pp.148-167, (2015).
- Tarek Gaber, Gehad Ismail, Ahmed M. Anter, Mona Soliman, Mona Ali, Noura Semary, Aboul Ella
Hassanien, Vaclav Snasel, “Thermogram Breast Cancer Prediction Approach based on Neutrosophic Sets and
Fuzzy C-Means Algorithm”, IEEE, 37th Annual International Conference of the IEEE Engineering in
Medicine and Biology Society (EMBS), Milano, Italy, pp.4254-4257, (2015).
42 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Climate change and its relations in
Egyptian agriculture
Mohamed Abd El Salam,)Ph.D. Student)
Institute of Statistical Studies and Research (ISSR), Cairo University(
Email: mzissr@yahoo.com
Abstract: Over the past fifty years, the world has demonstrated increased concern over the climate-change
phenomenon. In Scientific Research Group in Egypt (SRGE), we study the particulars of this phenomenon
with the aim of identifying how to cope with it and how to reduce its associated risks and its relations and
effects on agriculture in Egypt.
Mohamed Abd El Salam, is a Ph.D. student at Institute of Statistical Studies and
Research (ISSR), Cairo University. He holds a B.Sc. in Electrical engineering
at Faculty of Engineering, Alexandria University. He received his M.Sc. degree in 2012
in voice over wireless networks (WNs), his research interested in WNs, climate change
and thermal image processing.
- Mohamed Abdel Salam, Mahmood A.Mahmood, Yasser Mahmoud Awad, Maryam
Hazman, Nashwa El Bendary, Aboul Ella Hassanien, Mohamed F. Tolba and Samir
Mahmoud Saleh Climate recommender system for wheat cultivation in North Egyptian
Sinai Peninsula" the 5th International Conference on Innovations in Bio-Inspired
Computing and Applications, 22-24 June 2014, Ostrava, Czech Republic.
43 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Social Graph data mining
Ragia A. Ibrahim Institute of Statistical Studies and Research (ISSR), Cairo University (
Ragia A. Ibrahim, is a Ph.D. student at Institute of Statistical Studies and Research
(ISSR), Cairo University. She holds a bachelor degree in accounting from Ain Shams
University,Egypt. In addition to two Master degrees in Computer Science. The first
from Cairo University and the second from University of Louisville, USA, in
association with Regional Information Technology Institute (RITI). Her research
focuses on mining and modeling large social and information networks, their
evolution, and diffusion of information.
44 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Plant Diseases Identification/Image Processing
Usama mokhtar
Ph.D Student.
SRGE member (www.egyptscience.net) Emails: usamamokhtar@yahoo.com.
Abstract: Automatic detection of plant diseases is an essential research topic as it may
prove benefits in monitoring large fields of crops and thus automatically detect the
symptoms of diseases as soon as they appear on plant leaves. Therefore looking for fast,
automatic, less expensive and accurate method to detect disease is very important for
research issues. Many techniques can be used in that field like image processing. It can be used in
agricultural applications to detect and quantify affected area of leaf, stem and fruit. Also,
can be used to find shape and colour of affected area and so on.
Usama Mokhtar Hassa, was born in El Fayoum, Egypt in 1957. He
received his B.Sc. degree in 1997 from Faculty of Science and
Education, math and computer science Department, Cairo University,
Egypt. He Studied Computer Science at the Institute of Statistical
Studies and Research and received Specialization Diploma in
Computer Science in 2001.
He received M.Sc. degree in 2010, from Institute of Statistical
Studies and Research, Cairo University, Egypt. He started PH.Sc in
March 2012, at the Institute of Statistical Studies and Research,
Computer science Department, Cairo University, Egypt
Research Interest
1. Image Processing,
2. Data Mining.
3. Swarm optimization
Selected Publication:
1. Mokhtar, Usama, Nashwa El Bendary, Aboul Ella Hassenian, E. Emary, Mahmoud A.
Mahmoud, Hesham Hefny, and Mohamed F. Tolba. "SVM-Based Detection of Tomato Leaves Diseases." In Intelligent Systems' 2014, pp. 641-652. Springer International Publishing, 2015.
Publishing.
2. Mokhtar, U., Ali, M. A., Hassanien, A. E., & Hefny, H. (2015). Identifying Two of Tomatoes Leaf Viruses Using Support Vector Machine. In Information Systems Design and Intelligent Applications (pp. 771-782). Springer India.
3. Mokhtar, Usama, Mona AS Ali, Aboul Ella Hassenian, and Hesham Hefny. "Tomato leaves diseases detection approach based on Support Vector Machines." In 2015 11th International Computer Engineering Conference (ICENCO), pp. 246-250. IEEE, 2015.
45 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Complex Segmentation in Medical Imaging
Abdalla Mostafa Abdalla
Ph.D. Student - Computer Sciences
Member of Scientific Research Group in Egypt (SRGE)
Institute of statistical studies and researches, Cairo University, Egypt
E-mail:abdalla_mosta75@yahoo.com@gmail.com
The objective of medical image processing is to pave for a Computer-Aided diagnosis system (CAD). The
intended organ for me is liver. CAD system is seeking a reliable CT liver image segmentation, to separate
the liver from other organs, and segment the liver into a set of regions of interest (ROIs). Segmentation is the
main concern and implemented using traditional techniques and swarm intelligence. The segmentation is
done using iterative K-means, morphological operations and wolf local thresholding, combined with two
main segmentation methods, region growing and level set. Swarm intelligence techniques are new trend in
my work, including Artificial Bee colony and Grey wolf optimization. It is used as a clustering technique to
segment the liver from the abdomen in CT images. The optimization is also tested on the Arabic manuscripts
for better binarization.
Abdalla Mostafa Abdalla is a PhD student at the department of computer
science in Institute of Statistical Studies and Research (ISSR), Cairo
University. He graduated from the faculty of commerce 1985. In 2007 he got a
diploma in computer science from ISSR, Cairo university. Then in 2012, he
received his Master degree in computer science, Cairo University with thesis
titled “A Computer-Aided Diagnosis System in Medical Imaging.” Abdalla has
published 3 conference papers and one journal paper through his master.
Research interest 1- Medical imaging segmentation. 2- Natural language processing.
3- Swarm optimization techniques.
Publications:
1. Mostafa, A., M. A. Fattah, A. E. Hassanien, H. Hefny, and G. S. Shao Ying Zhu, "CT Liver
Segmentation Using Artificial Bee Colony Optimisation", 19th International Conference on
Knowledge Based and Intelligent Information and Engineering Systems, Procedia Computer
Science , Singapore, September, 2015.
2. Mostafa, A., M. A. Fattah, A. Ali, and A. E. Hassanin, "Enhanced Region Growing Segmentation
For CT Liver Images", the 1st International Conference on Advanced Intelligent Systems and
Informatics (AISI’15) Springer, . Beni Suef University, Beni Suef, Egypt , Nov. 28-30 , 2015.
46 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Computational Intelligence Approaches for
Bioinformatics Problems
Mahir Mohammed Sharif Adam
Assistant Lecturer (Ph.D Student)
Scientific Research group in Egypt (www.egyptscience.net)
Computer Science and Information Dept., ISSR, Cairo University
Email: mahiralsharif@yahoo.com, mahir.alsharif@egyptscience.net
Abstract:Computational intelligence is one branches of artificial intelligence, where well-crafted
algorithms are being developed that solve complex, computationally expensive problems that are
believed to require intelligence, has recently become the third method of scientific enquiry,
besides, theory and experimentation. Computational Intelligence is one of the most promising
tools today to attack the remaining hard problems in bioinformatics and human genetics (e.g.,
diseases discovery and susceptibility, protein enzyme classification and prediction, genes
interaction and dependability …). One of these approaches, develop and implement approach to
classify and predict the protein enzyme using one of machine learning methods(e.g., SVM, NN,
Decision Tree…) and extracted specific features from amino acid sequence to classify the protein
enzymes according to EC classes.
Keywords: Computational Intelligence, Bioinformatics, Machine Learning, Feature Extraction.
Mahir M. Sharif is an Assistant Lecturer in Computer Science Dept., Faculty of
Science and Technology, Omdurman Islamic University, Sudan. He received his
B.Sc. honour degree in May 2004 from Computer Science Dept., Faculty of Science
and Technology, Omdurman Islamic University, Sudan, and M.Sc. degree in Jan
2009 from Faculty of Computer Science and Information Technology, Computer
Science Dept., Alneelain University, Sudan. He received his pre-PhD in 2013 from
ISSR, Cairo University, Egypt. He is a member in SRGE (Scientific Research
Group in Egypt).
Research Interest 1)Bioinformatics, 2) Computational Intelligence, 3) Machine Learning.
Selected 2014 Publications
[1] Mahir M. Sharif, Alaa Tharwat, Islam I. Amin, Aboul Ella Hassanien and Hesham A. Hefeny. Enzyme
function classification based on sequence alignment. In Information Systems Design and Intelligent
Applications, Springer India. pp. 409-418. 2015.
[2] Mahir M. Sharif, Tharwat, A., Hassanien, A. E., & Hefeny, H. A. Automated Enzyme Function
Classification Based on Pairwise Sequence Alignment Technique. In: Intelligent Data Analysis and
Applications. Springer International Publishing, pp. 499-510. 2015.
47 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Historical Manuscripts Image Processing
Mohamed Abdel Fattah AbdelAzim
Ph.D. student (Computer Science)
Member of Scientific Research Group in Egypt (SRGE)
Faculty of Information& Computers, Mansoura, Egypt
E-mail: m_abdelfatah@gmail.com*mohabdelfatah8@gmail.com.m_abdelfatah@egyptscience.net
Abstract:In our work, an improved thresholding approach based on neutrosophic sets (NSs) and adaptive
thresholding is proposed. This is applied to degraded historical documents imaging and its performance
evaluated. The input RGB image is transformed into the NS domain, which is described using three subsets,
namely the percentage of truth in a subset, the percentage of indeterminacy in a subset, and the percentage of
falsity in a subset. The entropy in NS is employed to evaluate the indeterminacy with a _-mean operation
used to minimize indeterminacy. Finally, the historical document image is binarized using an adaptive
thresholding technique. Experimental results demonstrate that the proposed approach is able to select
appropriate image thresholds automatically and effectively, while it is shown to be less sensitive to noise and
to perform better compared with other binarization algorithms.
Mohamed Abdel Fattah is an assistant lecturer at the Department of computer
science. Cairo Higher institute for Eng., CS, MIS, new Cairo, Egypt. He received his
M.Sc. (image processing), Faculty of information computers, Mansoura Univ. In
2013. His Ph.D. Student in computer science (image processing), He also served as a
researcher in SRGE group. He has published over 8 papers in international
conferences.
Research Interest Research interests: Image Processing, Computer Vision, Big Data, Cloud Computing,
Rough sets.
Selected References:
- Aboul Ella Hassanien, Mohamed Abdelfatah, Khaled Amin, Shriihan Mohamed, A novel
hybrid binarization techniques for image of historical Arabic mansuscripts. Studies in
informatics and control, vol. 24(3), pp.271-282, 2015.
48 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Intelligent 3D digital watermarking and
applications
Mohammed Ahmed ElGayyar Assistant Lecturer, Department of Mathematics, Science Faculty, Cairo University
Member in the Scientific Research Group in Egypt (SRGE www.egyptscience.net)
Email: melgayar@sci.cu.edu.eg
Abstract. Digital watermarking is used for copyright protection, authentication, or information hiding
(Steganography). We can divide research in this field by two main factors: (1) The type of the media you target
(raster images, video, vector maps, ...etc) and (2) The type of watermark to be embedded (black and white
image, 3D image, bit stream, ...etc). Watermarking schemes include many processes, like watermark pickup
(watermark preparation process, 3D object watermark for example), pre processing the target (transformations
take place here), selection (the process of choosing where to embed the watermark in the target file, vertices
selection process in a 3D target for example), embedding (spatial or frequency/transform domain), and
extraction (blind, non-blind, or semi-blind).
Mohammed ElGayyar was born in ElMansoura, 1981. He received B.Sc. degree in 2003 and
received his M.Sc. degree in 2013 in Computer Science from Science Faculty, Cairo University,
Egypt. He is a member in the Scientific Research Group in Egypt (SRGE). He is a Ph.D. student
and Assistant Lecturer in Department of Mathematics, Science Faculty, Cairo University
1) Cryptology, 2)Steganography, 3) Digital Watermarking,4) Machine Learning, 5)
Clustering and
2) Classification
49 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Machine learning techniques in image
authentication
AlaaTharwat (Ph.D. Student)
Scientific Research Group in Egypt (Member)
Faculty of Engineering- Computer Dept., Suez Canal University
Email: alaa.osman@eng.suez.edu.eg ; engalaatharwat2hotmail.com
Abstract: Machine learning technique has many real applications and it is integrated into many
research areas. Machine learning is one of the fastest growing areas of computer science research.
Search engines, face recognition, DNA sequence analysis, speech and handwriting recognition,
credit card fraud detection, premature baby monitoring and autonomous locomotion are just some
of the applications in which machine learning is routinely used. My research focussing on applying
machine-learning techniques on many applications such as, biometrics and medical imaging. Also
his research focusing on image processing and use machine learning with it.
AlaaT.Abd- El Monaaim, received the B.Sc., M.Sc. degrees in faculty of
engineering- computer Dept. from the Mansoura University in 2002, 2009,
respectively. Currently, he is a teaching assistant at the Faculty of Engineering –
Computer Dept., Suez Canal University, Ismailia, Egypt. He worked as director
of digital library unit at Suez Canal University; currently he is a member in
SRGE (Scientific Research Group in Egypt). Hisresearch has been focused on
machine learning and their applications such as biometrics and medical imaging.
He has published over 6 papers in international journals and conferences.
Selected Publication 2015:
- Tarek Gaber, Alaa Tharwat and Aboul Ella Hassanien, One-Dimensional vs. Two-
Dimensional based Features: Plant IdentificationApproach, Journal of Applied Logic -
Elsevier, (accepted), 2016
- Alaa Tharwat Hani Mahdi, Adel El Hennawy, Aboul Ella Hassanien, Face Sketch
Recognition Using Local InvariantFeatures, 7th IEEE International Conference of Soft
Computing and Pattern Recognition,Kyushu University, Fukuoka, Japan, November 13 -
15, 2015
50 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Community detection in social networks
Ahmed Ibrahem Hafez.
Scientific Research Group in Egypt (Member) (Ph.d. student)
Faculty of Computer and Information, Minia University
Email: ah.hafez@gmail.com
Abstract: Social network analysis views social relationships in terms of network theory consisting
of nodes and ties (also called edges, links, or connections). Nodes are the individual actors within
the networks, and ties are the relationships between the actors. The resulting graph-based structures
are often very complex. Social network analysis concerns with modelling network dynamics,
centrality analysis, and influence modelling and community detection. Finding a community in a
social network is to identify a set of nodes such that they interact with each other more frequently
than with those nodes outside the group. Detecting cohesive groups in a social network remains a
core problem in social network analysis; also community detection can facilitate other social
computing tasks and is applied in many real world applications, for instance, classification and
recommendation in social networks, community detection also can be used to compress a huge
network, resulting in a smaller network. In recent years, community detection in complex networks
has attracted a lot of attention. The main reason is that communities are supposed to play special
roles in the structure-function relationship, and thus detecting communities (or modules) can be a
way to identify substructures which could correspond to important functions.
Ahmed Ibrahem Hafez received his B.Sc. degree in 2008 in Computer
Science from the Faculty of Computers and Information (FCI) - Minia
University, Egypt. And now he is a master student at FCI-Cairo
University, Egypt. Currently, he is working as teaching assistant in FCI-
Minia University, Egypt. His research interests are social network
analysis, parallel computing and computer Vision. He has been working in
some projects like computer video game called hyper-battle in his
graduation project and a modification to the spawn process in MPICH2 for
parallel computing. He attends the LinkSCEEM-2 CyI 2011 Winter
School at Cyprus Institute Nicosia, Cyprus.
Most recent publication:
- E. A. Hassan, A. I. Hafez, A. Hassanien and A. A. Fahmy. "Community Detection
Algorithm Based on Artificial Fish Swarm Optimization. " In Intelligent Systems' 2014, pp.
509-521. Springer International Publishing, 2015.
- Ahmed Ibrahem Hafez, Eiman Tamah Al-Shammari, Aboul Ella Hassanien, Aly A. Fahmy:
Community detection in social networks using logic-based probabilistic
programming. IJSNM 2(2): 158-172 (2015)
51 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Neutrosophic sets and its
applications
Sameh H.Basha (Ph.D. Student ) Member of Scientific Research Group in Egypt (SRGE)
Lecturer Assistant
Cairo University- Faculty of Science - Mathematics Department- Computer Science Division.
E-mail: SamehBasha@sci.cu.edu.eg
Abstract: Everything around us described by some data so data is very important and essential to deal with
anything and in every field whether industries or social. With the rapid development and wide application of
the internet and database technology, volume of data rapidly increased and we have a huge amount of data
wherever this data and within these masses of data lies a hidden information and this massive data
described by imprecision, incomplete, vagueness, and inconsistency which led to decrease accuracy and to
increase complexity when deal with this data. Soft computing differs from conventional (hard) computing in
that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation. In
effect, the role model for soft computing is the human mind. Neutrosophic is a new soft computing approach
which can deal with imprecision, incompleteness, vagueness, and inconsistency data.Neutrosophic logic was
developed to represent mathematical model of uncertainty, vagueness, ambiguity, imprecision,
incompleteness, inconsistency, redundancy and contradiction. There are many theories existing to handle
such imprecise information, such as fuzzy set theory, probability theory, probability theory, intuitionistic
fuzzy set theory, paraconsistent logic theory, etc. These theories can only handle one aspect of imprecise
problem but not the whole in one framework. Neutrosophic can handle incomplete information as wells
inconsistent information without danger of trivialization.
Sameh H.Basha, is a Lecturer Assistant at the Department of
Mathematics, Computer Science Division, Faculty of Science, Cairo
University, Egypt. He received the B.Sc., degree in mathematics and
computer science from faculty of science, Cairo University in 2005. Also
he got his Master Degree in Computer Sciences from Cairo University
with Thesis Title “Complexity Analysis Of Input Rules for Genetic -
Fuzzy Data Mining” in 2011. Sameh now Ph.d Student under
Supervision of Prof Aboul Ella Hassanien (Cairo University-Faculty of
Computers and Information- Information Technology Department), Prof
Laila Fahmie and Dr Areeg Saied (Cairo University-Faculty of Science-
Mathematics Department) in subject Neutrosophic set and its applications.
Research Interest: 1- Soft Computing (Fuzzy Logic and Genetic algorithm) 2- Rough Set
3- Neutrosophis set and Neutrosophic Logic 4- Data Mining
Selected Publication (2015):
52 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Chemoinformatics Algorithms
Ahmed Hassan Abu El-Atta (Ph.D. Student)
Member of Scientific Research Group in Egypt (SRGE)
Assistant Lecturer, Computer Science Department, Faculty of Computer and Information, Benha University, Benha,
Egypt
E-mail:
ahmed.hassan@egyptscience.net
ahmed_123_hasan@yahoo.com
ahmed.aboalatah@fci.bu.edu.eg
Abstract: Chemo-informatics (chemical informatics) is the field that seeks to use computer science, mathematics
and information techniques to solve some problems in the field of chemistry. Chemo-informatics has been applied in
Drug Discovery, Pesticide Design, Environment Protection, Material Design, Traditional Chinese Medicine (TCM),
Food Safety and etc., which relate to Chemistry. Chemo-informatics can also be described as a science aimed to
discover novel chemical entities that will result in the development of novel treatments for some medical needs.
Although Chemo-informatics also can be applied in many other fields that leads to design new molecules which can
be used in chemical and allied industries in various other forms. Kernels methods provide a powerful framework
combining machine learning and graph theory techniques. These kernels methods had led to impressive performance
results on many several chemo-informatics problems like biological activity prediction. The goal of the research is
how to use Chemo-informatics fields to make drug discovery easier. The study is intended to develop new graph
similarity algorithms or modifying existing algorithms to be used in drug discovery.
Ahmed Hassan, was born in Benha, Egypt in 1985. He received his B.Sc. degree in 2005 and M.Sc.
degree in 2011, from Faculty of Science, Computer Science Department, Benha University, Egypt.
He is an Assistant Lecturer at Computer Science Department, Faculty of Computers and
Information, Benha University, Egypt. He has authored/co-authored over 5 research publications in
peer-reviewed reputed journals and international conference proceedings.
Research Interest 1) Chemo-informatics, 2) Machine Learning, 3) Data Mining.
Selected Publication:
- Abu El-Atta AH, Moussa MI, Hassanien Aboul ella Predicting activity approach based on
new atoms similarity kernel function, Journal of Molecular Graphics and Modelling, Vl. 60,
pp. 55–62, 2015
53 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Establishment of a computerized system for
the rehabilitation of injured or with physical
deformities persons
Kadry Ali Ezzat
Biomedical Department
Higher Technological Institute 10th of Ramdan city
Email: kadry_ezat@hotmail.com
Abstract: One of the most critical problems in physicaldeformities is Scoliosis (from the Greek
skoliōsis meaning crooked condition) is a medical condition in which a person's spine is curved
from side to side. Although it is a complex three-dimensional deformity, on an x-ray, viewed from
the rear, the spine of an individual with a typical scoliosis may look more like an "S" or a "C" than
a straight line. It is typically classified as either congenital (caused by vertebral anomalies present
at birth), idiopathic (cause unknown, sub-classified as infantile, juvenile, adolescent, or adult
according to when onset occurred) or neuromuscular (having developed as a secondary symptom of
another condition, such as spina bifida, cerebral palsy, spinal muscular atrophy or physical trauma).
Our research is to establish computerized system to repair such this defects and rehabilitate the injured
persons
Kadry Ali Ezzat , was born in port-said, Egypt in 1982, He received his B.Sc.
degree in 2004, Teaching assistant in 2004 in biomedical department in higher
technological institute 10th of Ramdan city and M.Sc. degree in 2010 in biomedical
engineering Cairo university, the Thesis was with title ”3D segmentation and
visualization for mandible, maxilla and each teeth”, Now He is a assistant
literature in biomedical department in higher technological institute and he is Ph.D
student at biomedical engineering at Cairo university .His research interests are in
the areas of medical image processing , 3d segmentation and visualization in dental,
biomechanics ,artificial intelligence
54 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Social Network Analysis
Ramadan Babers
PhD Student, Faculty of Science, Helwan University, Cairo, Egypt
Member of Scientific Research Group in Egypt (SRGE)
E-mail: RamadanFM@gmail.com
Abstract: The investigation of the community structure has recently attracted considerable
attention in social networks analysis field. Social Networks defined by the interactions between
nodes, they are represented by a graph. The huge data of online social networks need to analyze and
discover the hidden relations between nodes. Our research’s objective is represented the community
detection as optimization problem and how to divide the network to communities of nodes.
Ramadan Babers received his B.Sc. degree in 1999 in Computer
Science from Faculty of Science - Helwan University, Egypt, and M.Sc.
degree in 2010 from Faculty of Science - Helwan University, Egypt.
Currently, he is PhD student in Faculty of Science - Helwan University,
Egypt. His research interests are social network analysis, community
detection in social networks and data mining.
Research
Interest
1) Social Network Analysis.
2) Data Mining.
Selected Publications:
1. Ramadan Babers, Neveen I. Ghali, Aboul Ella Hassanien, and Naglaa M. Madbouly, " Optimal
Community Detection Approach based on Ant Lion Optimization”, 11th International Computer
Engineering Conference, Cairo University, Egypt, December 29 - 30, 2015.
2. Ramadan Babers, Aboul Ella Hassanien, and Neveen I. Ghali, " A nature-inspired metaheuristic lion
optimization algorithm for community detection”, 11th International Computer Engineering
Conference, Cairo University, Egypt, December 29 - 30, 2015.
55 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Master
Students
56 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Bio-inspired versus Nature-inspired Optimizations for
Dimension Reduction and Parameters Tuning
Esraa Mohammed Elhariri, (M.Sc. Student)
Scientific Research Group in Egypt (Member)
Email: emh00@fayoum.edu.eg
Abstract: Any classification problem depends on a set of features used to represent an object. This
means that they have an influence on classification results, as features may be irrelevant, noisy and
redundant data, and this results in bad classification accuracy. Also many machine learning (ML)
techniques which play a very significant role in solving different classification, analysis and
forecasting problems in several areas have parameters. Setting these parameters correctly helps at
finding the best classification models, which result in the best classification accuracy. So, feature
selection and classifier parameters tuning play a crucial role in obtaining a high classification
accuracy. The aim of this research it to present a hybrid classification system based on bio-inspired
and nature-inspired optimization techniques such as grey wolf optimizer (GWO) and water wave
optimizer algorithms for dimension reduction and parameters tuning.
Esraa M. El-hariri received her B.Sc. degree in 2010 in Computer Science from the
Faculty of Computers and Information (FCI) - Fayoum University, Egypt and M.Sc.
degree in 2015 from FCI-Cairo University, Egypt. Currently, she is working as
Lecturer assistant in FCI-Fayoum University, Egypt. She is a member in the scientific
research group in Egypt(SRGE) (www.egyptscience.net). Her M.Sc. topic was about
"Content-based image retrieval for agricultural crops". Her main research interests are
Machine learning, Image and Signal Processing, Bio-inspired Optimization and Cloud
Computing Security
Selected Publications:
1. Esraa Elhariri, Nashwa El-Bendary, Aboul Ella Hassanien, A Hybrid Classification Model
for EMG signals using Grey Wolf Optimizer", the 1st International Conference on
Advanced Intelligent Systems and Informatics (AISI’15) Springer, Beni Suef University,
Beni Suef, Eg, Nov. 28-30, 2015.
2. Esraa Elhariri, Nashwa El-Bendary, Aboul Ella Hassanien, Grey Wolf Optimization for
One-Against-One Multi-class Support Vector Machines", 7th IEEE International
Conference of Soft Computing and Pattern Recognition, , Kyushu University, Fukuoka,
Japan, , November 13 - 15, 2015.
57 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Automatic Computer-Aided Diagnosis System in Medical Imaging
Gehad Ismail Sayed
Master Student, Faculty of Computers and Information, Cairo University
SRGE member (www.egyptscience.net)
Emails: gehadismail_fci@yahoo.com, DarkSpot_1993@yahoo.com
Abstract
Medical imaging is the process of creating visual representation of human body. It plays an
essential role in human body diagnosis and treatment. It is quite common that for the same set of
medical images, different doctors may come up with different diagnosis results. Computer-Aided
Diagnosis (CAD) has become one of the major research subjects in diagnostic medical imaging.
The main objective of CAD is to provide a fully automatic system which assist radiologists in
medical image interpretation through reducing the image reading time and improving the accuracy
and consistency of radiological diagnosis. This work introduces various CAD systems for different
medical imaging tools under two main approaches. These approaches are Neutrosophic Set and
Swarm Optimization approaches. Different medical imaging datasets such as CT, Thermal and
histopathology are used in these experiments. The experimental results show the efficiency of the
proposed CAD systems. Moreover, they have been compared with other related works.
Gehad Ismail Sayed was born in Cairo in 1993. She graduated from Cairo University
with B.Sc in Computer Science, 2013. She worked as software engineering for two
years. In 2014, she worked for Delta Software for ERP and Business Solution. In
2015, she worked for Sadeem Knowledge for Big Data and Analytic Solutions.
Currently she is information system specialist at Egyptian civil aviation authority,
master student at faculty of computers and information, Cairo University, IT
department and member at Scientific Research Group in Egypt (SRGE). Her research
interests include: Machine Learning, Data Analytics, Pattern Recognition and Image
Processing. She has many publications for this area.
List of Recent Publications:
[1] M. Ali, G. Sayed, T. Gaber, A. Hassanien, V. Snasel and L. Silva, "Detection of Breast
Abnormalities of Thermograms based on a New Segmentation Method", Proceedings of the
Federated Conference on Computer Science and Information Systems (ACSIS), IEEE, Vol. 5, Lodz,
Poland, PP. 255-261, 2015.
[2] T. Gaber, G. Sayed, A. Anter, M. Soliman, M. Ali, N. Semary, A. Hassanien and V. Snasel,
"Thermogram Breast Cancer Detection Approach Based on Neutrosophic Sets and Fuzzy C-Means
Algorithm", 37th Annual International Conference of the IEEE Engineering in Medicine and
Biology Society (EMBC), IEEE, PP. 4254-4257, Milano, Italy, 2015.
58 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Falling detection for seniors
Mai Nadi Ahmed (Master Student)
Member of Scientific Research Group in Egypt (SRGE)
E-mail:maisalem90@gmail.com
Abstract: The problem of the falls in the elderly has become a health care priority around the
world due to the related high social and economic costs. Fall detection has been recognized as an
effective approach for fall prevention. It can minimize fall related injuries by initiating timely
medical treatment. Besides, early detection of falls in the pre-impact phase can help activate on-
demand protection device, such as the inflatable airbag, so that any injuries caused by fall impacts
can be avoided. The elderly may not be able to activate a PERS (personal emergency response
systems) due to the potential loss of consciousness. Since fall-detection is an ill-defined process it
is also an interesting scientific problem. Many solutions have been proposed in detection and
prevention of falls and some excellent review studies were presented. The commonly solution is to
detect the falling by camera vision to protect the privacy of the person and enable the seniors more
comfortable than a ware sensors devices in everywhere in this body.
Mai Nadi Ahmed was born in Saudi Arabia in 1990. He received his B.Sc. degree in
2011. Now preparing M.Sc. at Faculty of Computers and Information, Information
Technology Department, Cairo University, Egypt.
Research Interest
Computer Vision, 2) Seniors field and 3) Image Processing.
Selected Publication
Mai Nadi, Nashwa El-Bendary, Aboul ella hassanien, Tai-Hoon Kim Falling Detection System
based on Machine Learning AITA2015 (2015 4th IEEE International Conference on Advanced
Information Technology and Sensor Application (AITS 2015)
59 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Community Detection within Social Networks
Eslam Ali Hassan (M.Sc. Student)
Faculty of Computer and Information, Cairo University
Scientific Research Group in Egypt (www.egyptscience.net)
Email: eslam.ali@fci-cu.edu.eg
Abstract. A social network is a graph made of nodes that are connected by one or more specific types of
relationships, such as values, friendship, work. The goal of community detection in networks is to identify
the communities by only using the information embedded in the network topology. Many methods have been
developed for the community detection problem. These methods use tools and techniques from disciplines
like physics, biology, applied mathematics, and computer and social sciences.One of the special interests in
social network analysis is discovering community structure. Community is a group of nodes that are tightly
connected to each other and loosely connected with other nodes. Community detection is the process of
network clustering into similar groups or clusters. Community detection has many applications including
realization of the network structure, detecting communities of special interest, visualization , etc.
Eslam graduated from the Faculty of Computers and Information – Cairo
University (FCI-CU) in 2007 with Excellent with Degree of Honour, He is
working as a teaching assistant at FCI-CU, and He is a member in the scientific
research group in Egypt (SRGE). His master topic is about "Community
Detection within Social Networks"; He is investigating Nature-Inspired
algorithms to detect communities within social networks.He has a good
programming experience using a variety of technologies; he is a certified Java
programmer (2010) from Sun Microsystems, and IBM Certified Mobile
Application Developer – IBM academic initiative (2014), he has worked in a
variety of projects using the .Net development stack.
Research Interest 1) Social Networks Analysis
2) Data Mining
3) Machine Learning
4) Computer Vision
List of publications 2015:
- E. A. Hassan, A. I. Hafez, A. Hassanien and A. A. Fahmy. "Community Detection Algorithm Based on
Artificial Fish Swarm Optimization" In Intelligent Systems' 2014, pp. 509-521. Springer International
Publishing, 2015.
60 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Social relationships in Reallity mining
Moustafa Zein
Scientific Research Group in Egypt (SRGE)
Computer Science Department, Thebes Academy
Cairo - Egypt E-mail: Moustafazn@gmail.com
Abstract: Social relationships or personalize interfaces is one of the most impressive topic in
human behavior studies. A social relationship modeling depends on relation modifiers. The
relation modifiers represent relation attitude and change. Some Social relationships modeling
is need to be identified and standardized circles of relations. In present study, we introduce a
relation modifiers modeller to identify circles of social relationships based on smartphone
photo gallery. There are four relation modifiers drived in study such as (degree of relation,
transitivity, decay or lifetime, and trust). These modifiers represent the main part of proposed
relation modifiers modeller. This is the first paper introduces relation modifiers identification
from smartphone photo gallery. The model results achieved accuracy up to 70% with decay
modifiers, and accuracy of trust modifier reached 98%.
Moustafa Zein graduated from faculty of computer and information, Cairo
University in 2012. I am teaching assistant at Thebes’s academy, computer
science Department and master student in Cairo university. I am a member of
the Reality Mining team in scientific research group in Egypt (SRGE). My main
research interests are Biomedical engineering, Cheminformatics, and Reality
Mining. I participated in publishing three papers in peer-review international
conference proceedings.
List of publications in 2015:
3. Moustafa Zein, Ammar Adl, Aboul ella hassanien, Tai-Hoon Kim, Friendship classification from
Psychological theories to computational model, 2015 Fourth IEEE International Conference on
Information Technology and Computer Science (ITCS 2015) 8-11 July 2015 in Kota Kinabalu, Kota
Kinabalu, Malaysia
4. Moustafa Zein, Ammar Adl, Amr Badr, Aboul ella Hassanien, Tai-Hoon Kim A Social Relationship
Modifiers Modeller, CIA 2015 (2015 3rd IEEE International Conference on Computer, Information and
Application (CIA 2015), 21-23 May 2015 in Yeosoo, Yeosoo, South Korea, pp. 33 – 37, 2015.
61 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Hydro informatics and aquatic weeds
prediction
Rania ElesawyAbdElrahim Master student Member of Scientific Research Group in Egypt (SRGE)
E-mail: elesawyrania@gmail.com
Abstract: Aquatic weeds are the greatest generator of biomass in aquatic environment which
motivation intelligent methods for prediction and estimation of indicators that affect the growth of
weeds. In this study a set of new interpolation methods are used and assessed over the study area for
predicting a set of chemical indicators that can predict and affect the growth of weeds. The used
methods are bi-harmonic, regularized spline with Tension, Barnes, tri-scatter, and Kriging. The
different interpolants are used to create thematic maps representing the different chemical indicators
that are sensed at discrete positions for supporting decision making. The performance of individual
interpolantsis assessed using mean square error over a set of test sites. Results prove that the Tri-
scatter interpolant is the one with best performance for all the sensed indicators while the
regularized spline performs well when the number of points for interpolation is
large enough. .
Rania E.Elesawy was born in Tripoli, Libya. Studied at Ain Shams University
Faculty of science Department of computer science and pure math, Studied
Information system at the Institute of Statistical Studies and Research Graduate
Specialization Diploma in information system 2011/2012. Pre Masters 2012/2013.
Started M.Sc.in March2014, at the Institute of Statistical Studies And Research,
information system Department, Cairo University, Egypt.
Research Interest
1) Machine Learning, 2) System Analysis,3) Knowledge Base System, 4) DataMining,5 ) E-
commerce&6) Expert System.
62 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
An Intelligent Diagnosis System for Heart Sound
Analysis
Ahmed Hamdy, Master Student.
Scientific Research Group in Egypt (Member)
Institute of Statistical Studies and Research, Cairo University (ISSR)
Email: ahamdy@fci-cu.edu.eg
Abstract:Truly, heart is successor to the brain in being the most significant vital organ in the body
of a human. Heart, being a magnificent pump, has his performance orchestrated via a group of
valves and highly sophisticated neural control. While the kinetics of the heart is accompanied by
sound production, sound waves produced, by the heart, are reliable diagnostic tools to check heart
activity. Chronologically, several data sets have been put forward to sneak on the heart
performance and lead to medical intervention whenever necessary. Research problem consists of
opening problem (valvular stenosis) and closing problem (valvular insufficiency).Research
objective is to deal with the heart opening and closing valves sounds problems, namely
insufficiency or regurgitation respectively, and stenosis of the 4 heart valves. The heart sounds data
set, utilized in this research, provides researchers with abundance of sound signals that was
classified using different classification algorithms as; SVM, decision tree, rotation forest, random
forest, etc.
Ahmed Hamdy El-Sayed a master student at Cairo University, Institute of
Statistical Studies and Research (ISSR), Computer Science Department. He is a
member in Scientific Research Group in Egypt (SRGE)www.egyptscience.net/.
His master topic in "Intelligent System for Heart Sound Analysis". His received
his B.Sc. degree from Faculty of Commerce, Cairo University 2001. He has
authored of 2 research papers in Federated Conference on Computer Science and
Information System (FedCSIS), Wroclaw 2012 and Krakow 2013, Poland
respectively. His research interested includes Bioinformatics, machine learning, and data mining.
63 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
-
An automatic flower classification
using machine learning algorithms
Mona Abbass
Master Computer Sciences (Database Management Systems)
Member in Scientific Research Group in Egypt (SRGE)
Central Laboratory for Agricultural Expert System, Agricultural Research Center
E-mail: Mona_abbass12@hotmail.com
Abstract: This work aims to develop an effective flower classification approach using machine learning
algorithms. Eight flower categories were analyzed in order to extract their features. Scale Invariant Feature
Transform (SIFT) and Segmentation based Fractal Texture Analysis (SFTA) algorithms are used to extract
flower features. The proposed approach consists of three phases namely: segmentation, feature extraction,
and classification phases. In segmentation phase, the flower region is segmented to remove the complex
background from the images dataset. Then flower image features are extracted. Finally for classification
phase, the proposed approach applied Support Vector Machine (SVM) and Random Forests (RF) algorithms
to classify different kinds of flowers. An experiment was carried out using the proposed approach on a
dataset of 215 flower images. It shows that Support Vector Machine (SVM) based algorithm provides better
accuracy compared to the Random Forests (RF) algorithm when using the SIFT as a feature extraction
algorithm, While Random Forests (RF) algorithm provides its better accuracy with SFTA. Moreover, the
system is capable of automatically recognize the flower name with a high degree of accuracy.
Mona Abbass is an assistant Researcher at Central Lab for Agricultural
Experts Systems, Ministry of Agriculture and Land Reclamation. She
received her Master Degree from faculty of science, Helwan University
with Thesis Title “Transaction Processing in Distributed Database
Systems”. She has published 4 papers in international conferences and
journals.
research interest 1) Database Management Systems, 2) Semantic Web, and 3) Image
Processing.
Selected Publication 2015:
64 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Swarms optimization techniques hybrid
with machine learning for feature selection
Waleed Yamany Ph.D. Student
Member of Scientific Research Group in Egypt (SRGE)
Faculty of Computers and Information, Fayoum University, Fayoum, Egypt.
Email: wsy00@fayoum.edu.eg.com
Abstract. Feature selection is one of the most essential problems in the fields of data mining,
machine learning and pattern recognition. The main purpose of feature selection is to determine a
minimal feature subset from a problem domain while retaining a suitably high accuracy in
representing the original features. In real world problems, feature selection is a must due to the
abundance of noisy, misleading or irrelevant features. By removing these factors, learning from data
techniques can useful greatly. The motivation of feature selection in data mining, machine learning
and pattern recognition is to reduce the dimensionality of feature space, improve the predictive
accuracy of a classification algorithm, and develop the visualization and the comprehensibility of
the induced concepts. We propose feature selection strategy based on machine learning including
rough set/neural networks and many optimization techniques such that bat, cuckoo, gray wolf
algorithms. This optimization algorithm find optimal regions of the complex search space through
the interaction of individuals in the population.it requires only primitive and easy mathematical
operators, and is computationally inexpensive in terms of both memory and runtime
Waleed Yamany received her B.Sc. with honors in 2007 from Faculty of
science, mathematics department, fayoum university, He received her Pre-Master
in 20 90 from Faculty of science, mathematics department, fayoum university, He
is a teaching assistant at faculty of computers & Information, Basic science
department, fayoum university since 2009, He is a member in the scientific
research group in Egypt (SRGE) (www.egyptscience.net). Her master topic is
about "Rough Set and Application". His main research interests are, Data Mining
and Optimization Techniques.
Research Interest 1) Machine Learning, 2) Image Processing,
3) Optimization Techniques, 4) Data Mining.
Selected publications 2015:
- E. Emary, Hossam M. Zawbaa, Waleed Yamany, Aboul Ella Hassanien Hybrid flower pollination
algorithm with rough sets for feature selection, 11th IEEE International Computer Engineering
Conference, Cairo, EGYPT December 29-30, pp. 278 - 283,2015
- Waleed Yamany, Mohammed Fawzy, Alaa Tharwat, Aboul Ella Hassanien Moth-Flame
Optimization for Training Multi-layer Perceptrons, 11th IEEE International Computer Engineering
Conference, Cairo, EGYPT December 29-30, pp. 267 – 272, 2015
65 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Feature selection and case retrieval
HebaAyeldeen, (M.Sc. Student)
Scientific Research Group in Egypt (Member)
Faculty of Computer and Information, Cairo University
Email: heba.ayeldeen@gmail.com
Abstract: Knowledge acquisition is considered as an extraordinary issue concerning organizations and decision
makers nowadays. Learning from previous failures and successes saves plenty of time in understanding
the problems and visualizing data. Finding the similarities between objects as well as knowledge
extraction sometimes is a complicated issue to handle concerning decision makers and executive
managers. Case-based reasoning as a concept covers almost a lot of technologies and techniques
including knowledge management, artificial intelligence, machine learning techniques as well as
database technology.
Heba Ayeldeen,is a master student at the Department of Information
Systems, Faculty of Computer Science and Information, Cairo University.
She received her B.S.c., degree in Information System from Faculty of
Computer Science and Information, Cairo University in 2008. The thesis
title is "Using Case-Based Reasoning for Decision Support". Heba has
published about 6 papers in Peer Reviewed International Conferences and
still working on more. Heba is working as well as SAP Business
Intelligence Consultant concerning with data visualization and Business
Object tools.
Selected Publications:
Heba Ayeldeen, Olfat Shaker, Osman Hegazy and Aboul Ella Hassanien, "Case-based
reasoning: A knowledge extraction tool to use" in Second International Conference on
Information Systems Design and Intelligent Applications – 2015, Springer, India, 2015.
Heba Ayeldeen, Osman Hegazy and Aboul Ella Hassanien, " Case selection strategy based
on K-means clustering" in Second International Conference on Information Systems Design
and Intelligent Applications – 2015, Springer, India, 2015.
66 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Case-based reasoning system for
assessing water pollution
Asmaa Hashem Abd El-tawab, M.Sc. Student.
Member of Scientific Research Group in Egypt (SRGE)
Faculty of Computers and Information, Fayoum University
Email: asmaa.sweidan@yahoo.com
Abstract: The monitoring of water quality is a great challenge today. To carry out chemical
analysis continuously is complex and expensive, and also provides limited data about the chemical
compounds which ignores the influence of those excluded in the analysis. Fish Liver and gills
observed microscopically showed increasing degrees of damage in the tissues in correlation with
the quality of water. So we use the fish liver and gills as a biomarker for water quality. This
research presents system using Case-based reasoning and machine learning to automate the process
of assessing water quality by examining and classifying different Fish liver and Gills
histopathology.
Asmaa Hashem Abd El-tawab, received her B.Sc. with honours in 2010 from
Faculty of Computers & Information, information system department, Fayoum
university, She received her Pre-Master in 2013 from Faculty of Computers &
Information, Information system department, Cairo university, She is a
demonstrator at faculty of computers & Information Fayoum university since
2010, She is a member in the scientific research group in Egypt (SRGE)
(www.egyptscience.net). Asmaa master topic is about “Case-based reasoning
System for Assessing Water Pollution".
Publications 2015
- Asmaa Hashem Sweidan, Nashwa El-Bendary, Aboul Ella Hassanien, Osman
Mohammed Hegazy, A. E.-K. Mohamed: Grey Wolf Optimizer and Case-Based
Reasoning Model for Water Quality Assessment. AISI 2015: 229-239
- Asmaa Hashem Sweidan, Nashwa El-Bendary, Osman Mohammed Hegazy, Aboul Ella
Hassanien: Biomarker-Based Water Pollution Assessment System Using Case-Based
Reasoning. ECC 2015: 547-557
67 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
A Recommender System for the
Rehabilitationof people with disabilities
Rehab Mahmoud Abdel Raheem (M.Sc. Student)
Member of Scientific Research Group in Egypt (SRGE)
Faculty of Computers and Information, Fayoum University
Email: eng.rehabmahmoud@gmail.com
Abstract: Disability affects people’s behavior in their life and their participation in daily activities specially
the injuries of spinal cord. The injuries of spinal cord may be caused by accidents or sports. Those types of
injuries have various effects on many sides in person life. Consequently, people with spinal cord injury
(SCI) have difficulty in participating in routine daily activities. Also they need different types of care to keep
their health status in progress. This may take a long time according to the type of their injury. So, a
recommender system for providing rehabilitation methods of patient with spinal cord injury diseases is
required. The International Classification for Functioningdisability and health (ICF) framework. ICF is a
standard classification system which aims to improve integration of health information, and ensuring the
collection of accurate health data.
Rehab Mahmoud Abdel Raheem, received her B.Sc. with honours in 2010
from Faculty of Computers & Information, information system department,
Fayoum university, She received her Pre-Master in 2013 from Faculty of
Computers & Information, Information system department, Cairo university,
She is a demonstrator at faculty of computers & Information Fayoum
university since 2010, She is a member in the scientific research group in
Egypt (SRGE) (www.egyptscience.net). Rehab master topic is about “A
Recommender System for the Rehabilitation of people with disabilities".
- Rehab Mahmoud, Nashwa El-Bendary, Hoda M. O. Mokhtar, Aboul Ella Hassanien,
Similarity Measures based Recommender System for Rehabilitation of People with
Disabilities. The 1st International Conference on Advanced Intelligent Systems and
Informatics (AISI’15) , Springer. Beni Suef University, Beni Suef, Egypt during Nov. 28-
30, 2015.
68 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Evolutionary particle swarm optimization for fast
fuzzy c-means clustering on liver CT images
Abder-Rahman Ali (Ph.D. Student)
Scientific Research Group in Egypt (SRGE)
Email: abder-rahman.a.ali@ieee.org
Abstract: An Evolutionary Particle Swarm Optimization based on the Fractional Order Darwinian
method for optimizing a Fast Fuzzy C-Means algorithm is being proposed. This research aims at
enhancing the performance of Fast Fuzzy C-Means, both in terms of the overall solution and speed.
To that end, the concept of fractional calculus is used to control the convergence rate of particles,
wherein each one of them represents a set of cluster centers. The proposed solution, denoted as
FODPSO-FFCM, is applied on liver CT images, and compared with Fast Fuzzy C-Means and
PSOFFCM, using Jaccard Index and Dice Coefficient. The computational efficiency is achieved by
using the histogram of the image intensities during the clustering process instead of the raw image
data.
Abder-RahmanAli, received his BSc in Computer Science in 2006 from the
University of Jordan,MSc Software Engineering in 2009 from DePaul University,
and is currently pursuinghis Ph.D. degree in France,in the area of fuzzy clustering
and discrete geometry of MRI and ultrasound imaging sequences for Hepa-
tocellular Carcinoma (HCC).He is very passionate to the idea of applying
computer science to medical imaging, and software engineering to medical device
software systems, in an eventual goal to come up with algorithms and systems that
aid in Computer Aided Diagnosis (CAD).
Selected publications:
- Mc Hugh, Martin andAli, Abder-Rahman and Mc Caffery, Fergal (2013) The Significance of
Requirements in Medical Device Software Development. In: EuroSPI 2013, 25-27 June, Dundalk,
Ireland.
- Abder-Rahman A. Ali, Thomas M. Deserno, "A Systematic Review of Automated Melanoma
Detection in Dermatoscopic Images and its Ground Truth Data", Proc. SPIE 8318, 83181I (2012)
69 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Swarm intelligence for image segmentation
Micael S. Couceiro,(Ph.D. Student)
Institute of Systems and Robotics
Faculty of Sciences and Technology, University of Coimbra, Portugal
Email: micaelcouceiro@isr.uc.pt
Abstract: Image segmentation plays an essential role in image analysis and, as such, it has been widely used
fortopological feature extraction, quality inspection, medical imaging, among many other applications.Given
its range of applicability, several image segmentation strategies were proposed over the last years,
comprising on threshold, regional, edge detection and clustering methods. However, regardless on the
approach, the automatic selection of a robust optimal method still remains a challenge in image
segmentation. Most traditional methods present several drawbacks, being most of the time susceptible to
suboptimal solutions or requiring a high computational power to achieve acceptable results. Therefore,
image segmentation techniques inspired by swarm intelligence have becomeincreasingly popular during the
last decade.These systems mimics the decentralized behavior of swarms of social insects, flocks ofbirds, or
schools of fish, presenting a higher level of robustness and flexibility than traditional techniques.
Micael S. Couceiro, was born in Étamps, France in 1984. He received his B.Sc.
degree in 2006, Teaching Licensure in 2008 and M.Sc. degree in 2010, all in
Electrical Engineering atthe Engineering Institute of Coimbra, Polytechnic
Institute of Coimbra (ISEC-IPC), Portugal. He is a researcher at the Institute of
Systems and Robotics (ISR),being currently finishing his Ph.D. on Electrical
and Computer Engineering, Automation and Robotics, at the Faculty of
Sciences and Technologies, University of Coimbra (FCTUC), Portugal. He has
authored/co-authored over 80 research publications in peer-reviewed reputed
journals, book chapters and conference proceedings.His research interests are in
the areas of swarm intelligence, robotics, automation,swarm intelligence, video
and image processing, biomimetics, sport sciences, applied mathematics and
others.
Selected publication:
- P. Ghamisi, M. S. Couceiro, F. M. L. Martins and J. A. Benediktsson. “Multilevel Image
Segmentation Based on Fractional-Order Darwinian Particle Swarm Optimization”, IEEE
Transactions on Geoscience and Remote Sensing, 99, pp. 1-13, 2013.
- M. S. Couceiro, G. Dias, R. Mendes & D. Araújo. “Accuracy of Pattern Detection Methods in the
Performance of Golf Putting", Journal of Motor Behavior, Vol. 45, No. 1, 2013.
- M S. Couceiro, R. P. Rocha, N. M. F, Ferreira & J. A. T. Machado. "Introducing the Fractional
Order Darwinian PSO", Signal, Image and Video Processing, Fractional Signals and Systems
Special Issue, Springer, 2012.
70 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Organize several workshops in the
Egyptian universities (full list of all organized local
workshops at the end of this report)
71 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Travelling with students to attend int.
conferences
72 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Organizing and chairing International
Conferences in Egypt (to support our
research community)
73 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
SRGE monthly meeting
74 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
SRGE Publications (2015)
1. Tarek Gaber, Aboul Ella Hassanien, Nashwa El bendary, Dey Nilanjan, the 1st international
conference on advanced Machine Intelligents and Informatics (AISI2015) 28-30 Nov. 2015,
Beni-Suef, Springer, 2015
2. Aboul Ella Hassanien, Eid Alamry, Swarm Intelligence: Principles, Advances, and
Applications, CRC – Taylor & Francis Group, 2015, ISBN 9781498741064 - CAT# K26721
3. Aboul-Ella Hassanien, Crina Grosan, Mohamed Fahmy Tolba, Applications of Intelligent
Optimization in Biology and MedicineL Current Trends and Open Problems, Intelligent
Systems Reference Library, Volume 96 2016 ISBN: 978-3-319-21211-1 (Print) 978-3-319-
21212-8 (Online)
4. Aboul Ella Hassanien, Ahmad Taher Azar, Vaclav Snasel, and Janusz Kacprzyk Big Data
in Complex System: challenges and opportunities, Big Data Sets (BDS) series by Springer,
Vol. 9, 2015, ISBN 978-3-319-11056-1
5. Aboul Ella Hassanien, Ahmad Taher Azar Brain Computer Interface: Trends and
applications, Intelligent Systems Reference Library, Springer, Vol. 74, 2015, ISBN 978-3-
319-10978-7
6. Ahmed Fouad Ali, Aboul Ella Hassanien: A Survey of Metaheuristics Methods for
Bioinformatics Applications.Applications of Intelligent Optimization in Biology and
Medicine 2016: 23-46
7. Ahmed Fouad Ali, Aboul Ella Hassanien: A Simplex Nelder Mead Genetic Algorithm for
Minimizing Molecular Potential Energy Function. Applications of Intelligent Optimization
in Biology and Medicine 2016: 1-21
8. Abder-Rahman Ali, Micael S. Couceiro, Ahmed M. Anter, Aboul Ella Hassanien: Particle
Swarm Optimization Based Fast Fuzzy C-Means Clustering for Liver CT
Segmentation. Applications of Intelligent Optimization in Biology and Medicine 2016: 233-
250
9. Mohamed Tahoun, Abd El Rahman Shabayek, Aboul Ella Hassanien, Eid Emary, Marcello
Maria Giovenco and Ralf Reulke Satellite Image Registration: A Comparative Study Using
Invariant Local Features, Image Feature Detectors: Foundations, Innovations, and
75 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Applications, Volume 630 of the series Studies in Computational Intelligence pp 135-171
Springer, 2016
10. Asmaa Osamaa, Shaimaa Ahmed El-Said and Aboul Ella HassanienEnergy-Efficient Routing
Techniques for Wireless Sensors Networks, In Handbook of Research on Emerging
Technologies for Electrical Power Planning, Analysis, and Optimization, IGI, 2016.
11. Sirshendu Hore, Tanmay Bhattacharjee, Nilanjan Dey, Ayan Banerjeei, S.R.Bhadra
Chaudhuri and Aboul Ella Hassanien Real Time Dactylology Based Selective Image
Encryption Using Speeded Up Robust Features Extraction Technique and Artificial Neural
Network , Image Feature Detectors: Foundations, Innovations, and Applications, Volume
630 of the series Studies in Computational Intelligence pp 203-226 Springer, 2016
12. Abdelhameed Ibrahim, Takahiko Horiuchi, Shoji Tominaga and Aboul Ella Hassanien
Spectral Invariant for Spectral Reflectance Images and Its Application: Image Feature
Detectors: Foundations, Innovations, and Applications, Volume 630 of the series Studies in
Computational Intelligence pp 227-254 Springer, 2016
13. Islam Ibrahim Amin, Aboul Ella Hassanien,Samar K. Kassim, and Hesham A. Hefny, Big
DNA Methylation Data Analysis and Visualizing in a Common Formof Breast Cancer,
Springer International Publishing Switzerland 375 A.E. Hassanien et al.(eds.) Big Data in
Complex Systems, Studies in Big Data 9, DOI: 10.1007/978-3-319-11056-1_13 (2015)
14. Mohamed Mostafa Eltaweel and Aboul Ella Hassanien, Key Pre-distribution Techniques for
WSN Security Services. In Bio-inspiring Cyber Security and Cloud Services: Trends and
Innovations, Intelligent Systems Reference Library, Springer,
15. Hannah Inbarani, S. Udhaya Kumar, Ahmad Taher Azar, Aboul Ella Hassanien, Hybrid
Rough-Bijective Soft Set-based Classification for Medical Diagnosis, TRANSACTION on
ROUGH SETS (Accepted), 2016
16. Mrutyunjaya Panda · Aboul Ella Hassanien · Ajith Abraham, Hybrid Data Mining
Approach For Image Segmentation Based Classification, International Journal of Rough
Sets and Data Analysis (accepted) 01/2016;
17. Asmaa Hashem Sweidan, Nashwa Mamdouh, El-Bendary, Osman Mohammed Hegazy;
Aboul Ella Hassanien, Abd El-karim Mohamed, .Hybrid-Biomarker Case-Based Reasoning
System for Water Pollution Assessment in Abou Hammad Sharkia, Egypt, Applied Soft
computing, 2015, (Available online 27 November 2015),
76 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
18. E. Emary, Hossam M. Zawbaa and Aboul Ella Hassanien, Binary grey wolf optimization
approaches for feature selection, Neurocomputing, Volume 172, 8 January 2016, Pages
371–381.
19. Shang-Ling Jui, Shichen Zhang, Weilun Xiong, Fangxiaoqi Yu, Mingjian Fu, Dongmei
Wang, Aboul Ella Hassanien and Kai Xiao Brain MR Image Tumor Segmentation with 3-
Dimensional Intracranial Structure Deformation Features, IEEE Intelligent
Systems, http://doi.ieeecomputersociety.org/10.1109/MIS.2015.93, 2015
20. Aboul Ella Hassanien, Eid Emary, Hossam M. Zawbaa: Retinal blood vessel localization
approach based on bee colony swarm optimization, fuzzy c-means and pattern search. J.
Visual Communication and Image Representation 31: 186-196 (2015)
21. Ahmad Taher Azar, Senthil kumar S, Hannah Inbarani H, Aboul Ella Hassanien,
Pessimistic Multi-granulation Rough set based Classification for Heart Valve Disease
Diagnosis, International Journal of Modelling, Identification and Controlm 2015
22. Amira S. Ashour, Sourav Samanta, Nilanjan Dey, Noreen Kausar, Wahiba Ben
Abdessalemkar, Aboul Ella Hassanien Computed Tomography Image Enhancement Using
Cuckoo Search: A Log TransformBased Approach, Journal of Signal and Information
Processing, 6(3), 244-257, 2015.
23. Manash Sarkar, Soumya Banerjee, Aboul Ella Hassanien, Evaluating the Degree of Trust
under Context Sensitive Relational Database Hierarchy Using Hybrid Intelligent Approach.
International Journal of Rough Sets and Data Analysis, 2(1), 1-22, January-June 2015
24. Aboul Ella Hassanien, Mohamed Abdelfatah, Khaled Amin, Shriihan Mohamed, A novel
hybrid binarization techniques for image of historical Arabic mansuscripts. Studies in
informatics and control, vol. 24(3), pp.271-282, 2015.
25. Shaimaa Ahmed El-said, Asmaa Osamaa, Aboul Ella Hassanien Optimized hierarchical
routing technique for wireless sensors networks, Soft Computing, 2015
26. Mohamed Mostafa Fouad, Václav Snášel and Aboul Ella Hassanien Energy-aware Sink
Node Localization Algorithm for Wireless Sensor Networks, Int. Journal of Distributed
Sensor Networks, 2015
27. Ahmed Radhwan, Mahmoud Kamel, Mohammed Y. Dahab, Aboul Ella Hassanien
Forecasting Exchange Rates: A Chaos-Based Regression Approach. Intelligent Approach.
International Journal of Rough Sets and Data Analysis, 2(1), 38-57, January-June 2015
77 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
28. Hannah Inbarani H, Selva Kumar, Aboul Ella Hassanien, Ahmad Taher Azar, Hybrid TRS-
PSO Clustering Approach for Web2.0 Social Tagging System. Intelligent Approach.
International Journal of Rough Sets and Data Analysis, 2(1), 22-37, January-June 2015
29. Abu El-Atta AH, Moussa MI, Hassanien Aboul ella Predicting activity approach based on
new atoms similarity kernel function, Journal of Molecular Graphics and Modelling, Vl. 60,
pp. 55–62, 2015
30. Nashwa El-Bendary, Esraa El hariri, Aboul Ella Hassanien and Amr Badr “Using
Machine Learning Techniques for Evaluating Tomato Ripeness”
Expert Systems With Applications, Vol. 42, pp.1892–1905 2015
31. Ahmed M. Anter, Aboul Ella Hassanien, Ahmad Taher Azar,
Mohamed Abu ElSoud, Automatic Liver Parenchyma Segmentation System from
Abdominal CT Scans using Hybrid Techniques, International Journal of Biomedical
Engineering and Technology, vol. 17(2), 2015.
32. Alaa Tharwat Hani Mahdi, Adel El Hennawy, Aboul Ella Hassanien, Face Sketch
Recognition Using Local InvariantFeatures, 7th IEEE International Conference of Soft
Computing and Pattern Recognition,Kyushu University, Fukuoka, Japan, November 13 -
15, 2015
33. Gehad Ismail ; Ahmed Anter ; Mona Soliman ; Mona Ali ; Noura
Semary ; Aboul Ella Hassanien ;Vaclav Snasel, Thermogram breast cancer prediction
approach based on Neutrosophic sets and fuzzy c-means algorithm, 37th Annual
International Conference of the IEEE On Engineering in Medicine and Biology Society
(EMBC), 25-29 Aug. pp. 4254 – 4257, 2015
34. Mohamed Abd Elfattah, Aboul Ella Hassanien, Abdalla Mostafa, Ahmed Fouad Ali,
Khalid M. Amin, Sherihan Mohamed, Artificial bee colony optimizer for historical Arabic
manuscript images Binarizaiton, 11th IEEE International Computer Engineering
Conference, Cairo, EGYPT December 29-30, pp. 251 - 255, 2015
35. Guangyao Dai, Zongmei Wang, Chao Yang, Hongbo Liu, Aboul Ella Hassanien, Wanqing
Yang A Multi-granularity Rough Set Algorithm for Attribute Reduction through Particles
78 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
Particle Swarm Optimization, 11th IEEE International Computer Engineering Conference,
Cairo, EGYPT December 29-30, pp. 303 – 307, 2015
36. Usama Mokhtar, Aboul Ella Hassanien, Mona A. S. Ali, Hesham Hefny Tomato leaves
diseases detection approach based on support vector machines, 11th IEEE International
Computer Engineering Conference, Cairo, EGYPT December 29-30, pp. 246 – 250, 2015
37. Mohamed Mostafa Fouad, Ahmed Ibrahem Hafez, Aboul Ella Hassanien, Vaclav Snasel
Grey Wolves Optimizer-based Localization Approach in WSNs, 11th IEEE International
Computer Engineering Conference, Cairo, EGYPT December 29-30, pp. 256 – 260, 2015
38. Cun Hang, Fei Hu, Aboul Ella Hassanien and Kai Xiao Texture-based Rotation-Invariant
Histograms of Oriented Gradients, 11th IEEE International Computer Engineering
Conference, Cairo, EGYPT December 29-30, pp. 223 – 228, 2015
39. Ramadan Babers, Aboul Ella Hassanien, Neveen I. Ghali Optimal Community Detection
Approach Based on Ant Lion Optimization, 11th IEEE International Computer
Engineering Conference, Cairo, EGYPT December 29-30, pp. 284 – 289,2015
40. Ramadan Babers, Aboul Ella Hassanien and Neveen I. Ghali A nature-inspired
metaheuristic lion optimization algorithm for community detection, 11th IEEE International
Computer Engineering Conference, Cairo, EGYPT December 29-30, pp, 217 – 222, 2015
41. Moataz Kilany ; Aboul Ella Hassanien ; Amr Badr, Accelerometer-based human activity
classification using Water Wave Optimization approach, 11th IEEE International
Computer Engineering Conference, Cairo, EGYPT December 29-30, pp, 175 - 180, 2015
42. Ahmed Ibrahem Hafez, Aboul Ella Hassanien, Hossam M. Zawbaa, E. Emary Hybrid
monkey algorithm with krill herd algorithm optimization for feature selection, 11th IEEE
International Computer Engineering Conference, Cairo, EGYPT December 29-30, pp. 273
– 277, 2015
43. Mona A. S. Alim Gehad Ismail Sayed ; Tarek Gaber ; Aboul Ella Hassanien ; Vaclav
Snasel ; Lincoln F. Silva Detection of breast abnormalities of thermos-grams based on a
79 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
new segmentation method, Federated Conference on Computer Science and Information
Systems (FedCSIS), pp. 255 – 261, 13-16 Sept. 2015
44. Hamdi A. Mahmoud, Hagar M. El Hadad; Farid Ali Mousa ; Aboul Ella Hassanien Cattle
classifications system using Fuzzy K- Nearest Neighbor Classifier, 2015 International
Conference on Informatics, Electronics & Vision (ICIEV), 15-18 June 2015, Fukuoka,
J\pan, pp.1-5, 2015
45. E. Emary, Hossam M. Zawbaa, Waleed Yamany, Aboul Ella Hassanien Hybrid flower
pollination algorithm with rough sets for feature selection, 11th IEEE International
Computer Engineering Conference, Cairo, EGYPT December 29-30, pp. 278 - 283,2015
46. Waleed Yamany, Mohammed Fawzy, Alaa Tharwat, Aboul Ella Hassanien Moth-Flame
Optimization for Training Multi-layer Perceptrons, 11th IEEE International Computer
Engineering Conference, Cairo, EGYPT December 29-30, pp. 267 – 272, 2015
47. Khaled Ahmed, Ahmed Ibrahem Hafez and Aboul Ella Hassanien A Discrete Krill Herd
Optimization Algorithm For Community Detection, 11th IEEE International Computer
Engineering Conference, Cairo, EGYPT December 29-30, pp. 297 - 302, 2015
48. Gehad Ismail Sayed, Mona Abdelbaset Ali, Tarek Gaber, Aboul Ella Hassanien and Vaclav
Snasel A Hybrid Segmentation Approach Based on Neutrosophic Sets and Modified
Watershed: A Case of Abdominal CT Liver Parenchyma, 11th IEEE International
Computer Engineering Conference, Cairo, EGYPT December 29-30, pp. 144 – 149, 2015
49. Gehad Ismail Sayed and Aboul Ella Hassanien Interphase Cells Removal from Metaphase
Chromosome Images based on Meta-Heuristic Grey Wolf Optimizer, 11th IEEE
International Computer Engineering Conference, Cairo, EGYPT December 29-30, pp. 261
– 266, 2015
50. Gehad Hassan, Aboul Ella Hassanien, Nashwa El-bendary and Ali Fahmy Blood vessel
segmentation approach for extracting the vasculature on retinal fundus images using particle
swarm optimization, 11th IEEE International Computer Engineering Conference, Cairo,
EGYPT December 29-30, pp. 290 – 296,2015
80 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
51. Asmaa Hashem Sweidan, Nashwa El-Bendary, Aboul Ella Hassanien, Osman Mohammed
Hegazy, Abd El-karim Mohamed, Water Quality Classification Approach based on Bio-
inspired Gray Wolf Optimization, 7th IEEE International Conference of Soft Computing
and Pattern Recognition, Kyushu University, Fukuoka, Japan, November 13 - 15, 2015,
52. Esraa Elhariri, Nashwa El-Bendary, Aboul Ella Hassanien, Ajith Abraham, Grey Wolf
Optimization for One-Against-One Multi-class Support Vector Machines 7th IEEE
International Conference of Soft Computing and Pattern Recognition, Kyushu University,
Fukuoka, Japan, November 13 - 15, 2015,
53. Ahmed Ibrahem Hafez, Hossam M. Zawbaa, E. Emary, Hamdi A. Mahmoud, Aboul Ella
Hassanien, An innovative approach for feature selection based on chicken swarm
optimization, 7th IEEE International Conference of Soft Computing and Pattern
Recognition, Kyushu University, Fukuoka, Japan, November 13 - 15, 2015,
54. Sara Yassen, Tarek Gaber, Aboul Ella Hassanien, Integer Wavelet Transform for Thermal
Image Authentication, 7th IEEE International Conference of Soft Computing and Pattern
Recognition, Kyushu University, Fukuoka, Japan, November 13 - 15, 2015,
55. Alaa Tharwat , Hossam M. Zawbaa ; Tarek Gaber ; Aboul Ella Hassanien ; Vaclav
SnaselAutomated zebrafish-based toxicity test using Bat optimization and AdaBoost
classifier, 11th IEEE International Computer Engineering Conference, Cairo,
EGYPT December 29-30, pp. 169 – 174, 2015
56. Hossam M. Zawbaa, E. Emary, Aboul Ella Hassanien, B. PARV, A wrapper approach for
feature selection based on swarm optimization algorithm inspired from the behavior of
social-spiders, 7th IEEE International Conference of Soft Computing and Pattern
Recognition, Kyushu University, Fukuoka, Japan, November 13 - 15, 2015,
57. Rehab Mahmoud, Nashwa El-Bendary, Hoda M. O. Mokhtar, Aboul Ella Hassanien,
Similarity Measures based Recommender System for Rehabilitation of People with
Disabilities. The 1st International Conference on Advanced Intelligent Systems and
Informatics (AISI’15) , Springer. Beni Suef University, Beni Suef, Egypt during Nov. 28-
30, 2015.
81 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
58. Tarek Gaber, Taras Kotyk, Nilanjan Dey, Amira Ashour, Anghel Drugarin Cornelia
Victoria, Aboul Ella Hassanienand Vaclav Snasel, Detection of Dead stained microscopic
cells based on Color Intensity and Contrast, the 1st International Conference on Advanced
Intelligent Systems and Informatics (AISI’15) , Springer. Beni Suef University, Beni Suef,
Egypt during Nov. 28-30, 2015.
59. Abdalla Mostafa, Mohamed Abd Elfattah, Ahmed Ali and Aboul Ella Hassanin Enhanced
Region Growing Segmentation For CT Liver Images, the 1st International Conference on
Advanced Intelligent Systems and Informatics (AISI’15) Springer. Beni Suef University, Beni Suef,
Egypt during Nov. 28-30, 2015.
60. Moustafa Ahmed, Ahmed Hafez, Mohamed Elwakil,Aboul Ella Hassanien and Ehab
Hassanien A Multi-Objective Genetic Algorithm for Community Detection in
Multidimensional Social Network, the 1st International Conference on Advanced Intelligent
Systems and Informatics (AISI’15) Springer. Beni Suef University, Beni Suef, Egypt during Nov.
28-30, 2015.
61. Abdelhameed Ibrahim, Tarek Gaber, Takahiko Horiuchi, Vaclav Snasel and Aboul Ella
Hassanien Human Thermal Face Extraction Based on SuperPixel Technique , the 1st
International Conference on Advanced Intelligent Systems and Informatics (AISI’15) Springer.
Beni Suef University, Beni Suef, Egypt during Nov. 28-30, 2015.
62. Shichen Zhang, Fei Hu1, Shang-Ling Jui1, Aboul Ella Hassanien, and Kai Xiao
Unsupervised Brain MRI Tumor Segmentation with Deformation-Based Feature, the 1st
International Conference on Advanced Intelligent Systems and Informatics (AISI’15) Springer. Beni
Suef University, Beni Suef, Egypt during Nov. 28-30, 2015.
63. Gehad Ismail Sayed and Aboul Ella Hassanien Adaptive particle swarm optimization
approach for CT Liver Parenchyma segmentation, the 1st International Conference on
Advanced Intelligent Systems and Informatics (AISI’15) Springer. Beni Suef University, Beni Suef,
Egypt during Nov. 28-30, 2015.
64. Asmaa Hashem Sweidan, Nashwa El-Bendary, Aboul Ella Hassanien, Abd El-Karim
Mohamed and Osman Hegazy Grey wolf optimizer and case-based reasoning model for
82 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
water quality assessment, the 1st International Conference on Advanced Intelligent Systems and
Informatics (AISI’15) Springer. Beni Suef University, Beni Suef, Egypt during Nov. 28-30, 2015.
65. Waleed Yamany, Eid Emary and Aboul Ella Hassanien New Rough Set Attribute
Reduction Algorithm based on Grey Wolf Optimization, the 1st International Conference on
Advanced Intelligent Systems and Informatics (AISI’15) Springer. Beni Suef University, Beni Suef,
Egypt during Nov. 28-30, 2015.
66. M. Abdelazeem, E Emary and Aboul Ella Hassanien A hybrid Bat-regularized Kaczmarz
Algorithm to Solve Ill-posed Geomagnetic Inverse Problem, the 1st International Conference
on Advanced Intelligent Systems and Informatics (AISI’15) Springer. Beni Suef University, Beni
Suef, Egypt during Nov. 28-30, 2015.
67. Mohamed Mostafa Fouad, Hossam M. Zawbaa, Tarek Gaber, Vaclav Snasel and Aboul
Ella Hassanien A Fish Detection Approach Based on BAT Algorithm, the 1st International
Conference on Advanced Intelligent Systems and Informatics (AISI’15) Springer. Beni Suef
University, Beni Suef, Egypt during Nov. 28-30, 2015.
68. Esraa Elhariri, Nashwa El-Bendary and Aboul Ella Hassanien, A Hybrid Classification Model
for EMG signals using Grey Wolf Optimizer, the 1st International Conference on Advanced
Intelligent Systems and Informatics (AISI’15) Springer. Beni Suef University, Beni Suef, Egypt
during Nov. 28-30, 2015.
69. Alaa Tharwat, Hani Mahdi, Adel El Hennawy, Aboul Ella Hassanien Face Sketch Synthesis and
Recognition Based on Linear Regression Transformation and Multi-Classifier Technique the 1st
International Conference on Advanced Intelligent Systems and Informatics (AISI’15) Springer. Beni
Suef University, Beni Suef, Egypt during Nov. 28-30, 2015.
83 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
70. Tarek Gaber, Alaa Tharwat, Vaclav Snasel, Aboul Ella Hassanien Plant Identification: Two
Dimensional-Based Vs. One Dimensional-Based Feature Extraction Methods, 10th International
Conference on Soft Computing Models in Industrial and Environmental Applications Volume 368 of
the series Advances in Intelligent Systems and Computing pp 375-385, 2015
71. Mai Nadi, Nashwa El-Bendary, Aboul ella hassanien, Tai-Hoon Kim Falling Detection System
based on Machine Learning AITA2015 (2015 4th IEEE International Conference on Advanced
Information Technology and Sensor Application (AITS 2015)
72. Tarek Gaber, Alaa Tharwat, Abdelhameed Ibrahim, Vaclav Snasel, Aboul Ella Hassanien Human
Thermal Face Recognition Based on Random Linear Oracle (RLO) Ensembles, 2015 IEEE
International Conference on Intelligent Networking and Collaborative Systems, 2-4 September
2015, Taipei, Taiwan pp. 91-98, 2015.
73. Shaimaa Ahmed, Tarek Gaber, Alaa Tharwat, Aboul Ella Hassanien, and Vaclav Snasel, Muzzle-
based Cattle Identification using Speed up Robust Feature Approach, 2015 IEEE International
Conference on Intelligent Networking and Collaborative Systems, 2-4 September 2015, Taipei,
Taiwan pp. 99-104, 2015.
74. Abdalla Mostafaa, Ahmed Fouadb, Mohamed Abd Elfattahc , Aboul Ella Hassaniend, Hesham
Hefnya , Shao Ying Zhue , Gerald Schaefe, CT Liver Segmentation using Artificial Bee Colony
Optimisation, 19th International Conference on Knowledge Based and Intelligent Information and
Engineering Systems, Procedia Computer Science 60 ( 2015 ) 1622 – 1630
75. Abdalla Mostafa, Mohamed Abd Elfattah, Ahmed Fouad, Aboul ella Hassanien, Tai-Hoon Kim
Region Growing Segmentation with Iterative K-means For CT Liver Images by , (2015 4th IEEE
International Conference on Advanced Information Technology and Sensor Application (AITS
2015), pp. 88 – 91, 2015.
76. F. Eid, aboul ella Hassanien, Tai-hoon kim Leaf plant identification system based on hidden nave ,
(2015 4th IEEE International Conference on Advanced Information Technology and Sensor
Application (AITS 2015)
77. Moustafa Zein, Ammar Adl, Aboul ella hassanien, Tai-Hoon Kim, Friendship classification from
Psychological theories to computational model, 2015 Fourth IEEE International Conference on
Information Technology and Computer Science (ITCS 2015) 8-11 July 2015 in Kota Kinabalu, Kota
Kinabalu, Malaysia
84 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
78. Fatma Ismail, Eslam Ali Hassan, Aboul ella hassanien, Tai-Hoon Kim Blog Clustering with
Committee Approach, 2015 Fourth IEEE International Conference on Information Technology and
Computer Science (ITCS 2015) 8-11 July 2015 in Kota Kinabalu, Kota Kinabalu, Malaysia
79. Gehad Ismail, Moan Ali, Aboul ella hassanien, Tai-Hoon Kim Automatic Mitosis Detection and
Counting Approach for Breast Cancer Histopathology Slide Imaging using Neutrosophic Set, 2015
Fourth IEEE International Conference on Information Technology and Computer Science (ITCS
2015) 8-11 July 2015 in Kota Kinabalu, Kota Kinabalu, Malaysia
80. Heba AllaEdin, Mohamed Abd Elfattah, Olfat Shaker, Aboul ella Hassanien, Tai-Hoon Kim Case-
based Retrieval Approach of Clinical Breast Cancer Patients, CIA 2015 (2015 3rd IEEE
International Conference on Computer, Information and Application (CIA 2015), 21-23 May 2015
in Yeosoo, Yeosoo, South Korea
81. Moataz Kilany, Ammar Adl, Aboul ella hassanien, Tai-Hoon Kim Towards a Computational
Human Behavioral Model, CIA 2015 (2015 3rd IEEE International Conference on Computer,
Information and Application (CIA 2015), 21-23 May 2015 in Yeosoo, Yeosoo, South Korea)
82. Moustafa Zein, Ammar Adl, Amr Badr, Aboul ella Hassanien, Tai-Hoon Kim A Social
Relationship Modifiers Modeller, CIA 2015 (2015 3rd IEEE International Conference on Computer,
Information and Application (CIA 2015), 21-23 May 2015 in Yeosoo, Yeosoo, South Korea, pp. 33
– 37, 2015.
83. Moustafa Zein. Aboul Ella Hassanien, Amr Badr, Tai-Hoon Kim Human activity classification
approach on Smartphone using Monkey search algorithm. 2015 Seventh IEEE international
Conference on Advanced Communication and Networking (ACN 2015). 8-11 July 2015 in Kota
Kinabalu, Kota Kinabalu, Malaysia
84. Ahmed M. Anter, Aboul Ella Hassanien, Mohamed Abu ElSoud, Tai-Hoon Kim. Feature selection
approach based on social spider algorithm: Case study on Abdominal CT liver tumor, 2015 Seventh
IEEE International Conference on Advanced Communication and Networking (ACN 2015). 8-11
July 2015 in Kota Kinabalu, Kota Kinabalu, Malaysia
85. Waleed Yamany, Tarek Gaber Aboul Ella Hassanien and Tai-Hoon Kim, An innovative approach for
attribute reduction based on a new initialization of Cuckoo Search Algorithm, 2015 Fourth IEEE
International Conference on Sensor and Its Applications (SIA 2015). 9-11 July 2015 in Oakland
University, Michigan, USA
85 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
86. Gehad Ismail Sayed, Aboul Ella Hassanien and Tai-Hoon Kim, Fuzzy C-means and Grey Wolf
Optimizer for Abdominal CT Liver Parenchyma Segmentation, 2015 Fourth IEEE International
Conference on Sensor and Its Applications (SIA 2015). 9-11 July 2015 in Oakland University,
Michigan, USA
87. Mona A. S. Ali, M.I Shaalan, Aboul Ella Hassanien and Tai-Hoon Kim, A Simple Approach for
Segmentation and Removal of Interphase Cells from Chromosome Images, 2015 Fourth IEEE
International Conference on Sensor and Its Applications (SIA 2015). 9-11 July 2015 in Oakland
University, Michigan, USA
88. Alaa Tharwat, Abdelhameed Ibrahim, Aboul Ella Hassanien, Gerald Schaefer: Ear Recognition
Using Block-Based Principal Component Analysis and Decision Fusion. 6th International
Conference Pattern Recognition and Machine Intelligence - PReMI 2015, Warsaw, Poland, June 30
- July 3, 2015, pp,246-254
89. Eid Emary, Hossam M. Zawbaa, Kareem Kamal A. Ghany, Aboul Ella Hassanien, Bazil Pârv: Firefly
Optimization Algorithm for Feature Selection. Proceedings of the 7th Balkan Conference on
Informatics BCI 2015: 26
90. Fatma Yakoub, Moustafa Zein, Khaled Yasser, Ammar Adl and Aboul Ella Hassanien Predicting
Personality Traits and Social Context Based on Mining the Smartphones SMS Data, Proceedings of
the Second Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2015, pp.
511-521, June 29 - July 1, 2015, Ostrava, Czech Republic, 2015
91. Mahir M. Sharif, Alaa Tharwat, Aboul Ella Hassanien and Hesham A. H efeny Automated Enzyme
Function Classification Based on Pairwise Sequence Alignment Technique, Proceedings of the
Second Euro-China Conference on Intelligent Data Analysis and Applications (Springer), ECC 2015,
pp. 449-510, June 29 - July 1, 2015, Ostrava, Czech Republic, 2015.
92. Asmaa Hashem Sweidan, Nashwa El-Bendary, Osman Mohammed Hegazy, Aboul Ella Hassanien,
and Vaclav Snasel Water Pollution Detection System based on Fish Gills as a Biomarker, the
International Conference on Communication, Management and Information Technology
(ICCMIT2015), Journal of Procedia Computer Science by ELSEVIER, 2015
93. Gehad Hassan, Nashwa El-Bendary, Aboul Ella Hassanien, Ali Fahmy, Abullah M.Shoeb and Vaclav
Snasel Retinal blood vessel segmentation approach based on mathematical morphology, the
86 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
International Conference on Communication, Management and Information Technology
(ICCMIT2015), Journal of Procedia Computer Science by ELSEVIER, 2015
94. Esraa Elhariri, Nashwa El-Bendary, Aboul Ella Hassanienc, and Vaclav Snasel An Assistive Object
Recognition System for Enhancing Seniors Quality of Life, the International Conference on
Communication, Management and Information Technology (ICCMIT2015), Journal of Procedia
Computer Science by ELSEVIER, 2015
95. Moustafa Zein, Fatma Yakouba, Ammar Adlb, Aboul Ella Hassanien, Vaclav Snasel Identifying
Circles of Relations from Smartphone Photo Gallery, the International Conference on
Communication, Management and Information Technology (ICCMIT2015), Journal of Procedia
Computer Science by ELSEVIER, 2015
96. E.Emary, Waleed Yamany,Aboul Ella Hassanien and Vaclav Snasel Multi-Objective Gray-Wolf
Optimization for Attribute Reduction, the International Conference on Communication,
Management and Information Technology (ICCMIT2015), Journal of Procedia Computer Science by
ELSEVIER, 2015
97. Alaa Tharwat, Tarek Gaber, Mohamed Mostaf Fouad, Vaclav Snasel, Aboul Ella Hassanien Towards
an Automated Zebrafish-based Toxicity Test Model Using Machine Learning, the International
Conference on Communication, Management and Information Technology (ICCMIT2015), Journal
of Procedia Computer Science by ELSEVIER, 2015
98. Taras Kotyk, Sayan Chakraborty, Nilanjan Dey, Tarek Gaber, Aboul Ella Hassanien, Vaclav Snasel
Semi-automated system for Cup to Disc measurement for Diagnosing Glaucoma using
Classification Paradigm, Second International Afro-European Conference for Industrial
Advancement, September 9-11, 2015, Villejuif, France
99. Mohamed Mostafa Fouad, Vaclav Snasel and Aboul Ella Hassanien An Adaptive PSO-based Sink
Node Localization Approach for Wireless Sensor Networks, Second International Afro-European
Conference for Industrial Advancement, September 9-11, 2015, Villejuif, France
100. Rehab Mahmoud, Nashwa El-Bendary, Hoda M.O. Mokhtar, Aboul Ella Hassanien and Hala
A. Shaheen Machine Learning-Based Measurement System for Spinal Cord Injuries Rehabilitation
Length of Stay , Proceedings of the Second Euro-China Conference on Intelligent Data Analysis and
Applications, ECC 2015, pp. 523-534, June 29 - July 1, 2015, Ostrava, Czech Republic, 2015
87 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
101. Reham Gharbia, Ali Hassan El Baz, Aboul Ella Hassanien and Vaclav Snasel Region-based
Image Fusion Approach of Panchromatic and Multi-spectral Images, Proceedings of the Second
Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2015, pp. 535-545,
June 29 - July 1, 2015, Ostrava, Czech Republic, 2015
102. Asmaa Hashem Sweidan, Nashwa El-Bendary, Osman Mohammed Hegazy and Aboul Ella
Hassanien Biomarker-Based Water Pollution Assessment System Using Case-Based Reasoning ,
Proceedings of the Second Euro-China Conference on Intelligent Data Analysis and Applications,
ECC 2015, pp. 547-557, June 29 - July 1, 2015, Ostrava, Czech Republic, 2015
103. Alaa Tharwat, Tarek Gaber, Aboul Ella Hassanien, M. K. Shahin, Basma Refaat SIFT-
Based Arabic Sign Language Recognition System, Afro-European Conference for Industrial
Advancement Advances in Intelligent Systems and Computing Volume 334, pp 359-370,
2015.
104. Zhengqiong Zhu; Zongmei Wang; Tiancheng Li; Xingyu Wang; Hongbo
Liu;Hassanien, A.E.; Wanqing Yang, Multi-knowledge extraction algorithm using Group
Search Optimization for brain dataset analysis 2015 2nd International Conference on
Computing for Sustainable Global Development (INDIACom) 11-13 March, pp. 1891 –
1896, 2015
105. E. Emary, Hossam M. Zawbaa, Crina Grosan, Aboul Ella Hassenian, Feature
Subset Selection Approach by Gray-Wolf Optimization, Afro-European Conference for
Industrial Advancement Advances in Intelligent Systems and Computing Volume 334, pp
1-13, 2015.
88 | SRGE Annual Report 2016
Prof. Dr. Aboul Ella Hassanien ©SRGE2016 – www.egyptscience.net
العلمية المصرية البحثيةالمجموعة Scientific Research Group in Egypt
www.egyptscience.net
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