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The Smart Helmet System: Towards Providing Safer Construction Work Sites
Malak Ahmed;Haya Al-Korki;Danah Al-Hazza;Catherine El-Neaman;Mohammed El-Abd;Seyed Esmaeili
2024 IEEE Middle East Conference on Communications and Networking (MECOM)
Year: 2024 | Conference Paper |
Due to industrialization and the exponential increase in population, the demand for residential and commercial structures have considerably increased. However, during the process of developing these buildings, there are numerous risks/obstacles that confront/challenge the individuals working at the specified construction sites. The innovative features in the “Smart Helmet” essentially alleviates t...Show More
SkyPhoenix: The Anti-Drone Defense System
Naser Mahdi;Mohammad Omar;Ahmed AboElhiba;Dana Alnobani;Abeer Imdoukh;Mohammed El-Abd
2024 IEEE Middle East Conference on Communications and Networking (MECOM)
Year: 2024 | Conference Paper |
Several unmanned aerial vehicles (UAVs) or drones can hover around restricted areas or perform illegal or disruptive operations, steal critical information, affect normal operational flows within organizations, or even invade individuals’ privacy. Such vehicles can traverse areas beyond human reach, such as unfriendly terrain or otherwise hazardous areas. With the increase of incidents where such ...Show More
Roads: Road Assistance for Driver Safety
Mounib Khanafer;Farah Khalil;Kinda Waleed;Reem Hamed;Aya Rezk;Mohammed El-Abd
2024 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)
Year: 2024 | Conference Paper |
The world is currently struggling with numerous tragic incidents on the roads and escalating difficulties in effectively managing road traffic. Li-Fi, or Light Fidelity, is a wireless communication technology that utilizes visible light, infrared, and ultraviolet spectrum to transmit data. V2V (Vehicle-to-Vehicle) communication refers to the exchange of data between vehicles using wireless communi...Show More
A Neutrosophic Evaluation Model for Blockchain Technology in Supply Chain Management
Nada A. Nabeeh;Mai Mohamed;Ahmed Abdel-Monem;Mohamed Abdel-Basset;Karam M. Sallam;Mohammed El-Abd;Ali Wagdy
2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
Nowadays, firms are trying to execute and use blockchain technology (BT) for rising the products and service goodness in the supply chain (SC). Based on the specific requirements, the BT can be used in several areas. The BT assets various segments of Supply Chain Management (SCM) with consideration of several effective features that are characterized to be multi-criteria decision making (MCDM) iss...Show More
A Comparative Analysis for a Novel Hybrid Methodology using Neutrosophic theory with MCDM for Manufacture Selection
Nada A. Nabeeh;Ahmed Abdel-Monem;Mai Mohamed;Karam M. Sallam;Mohamed Abdel-Basset;Mohammed El-Abd;Ali Wagdy
2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Year: 2022 | Conference Paper |
The rapid growth of economic makes the process of manufacturing become a political, social, and community concerns. The manufacture selection is a complex multi-criteria decision making (MCDM) issue. The achievement of optimum alternative with respect to manufacture criteria have various diverse procedures. However, recognizing suitable MCDM methods to be adequate for manufacture process is critic...Show More
IMODEII: an Improved IMODE algorithm based on the Reinforcement Learning
Karam M. Sallam;Mohamed Abdel-Basset;Mohammed El-Abd;Ali Wagdy
2022 IEEE Congress on Evolutionary Computation (CEC)
Year: 2022 | Conference Paper |
Cited by: Papers (4)
The success of differential evolution algorithm depends on its offspring breeding strategy and the associated control parameters. Improved Multi-Operator Differential Evolution (IMODE) proved its efficiency and ranked first in the CEC2020 competition. In this paper, an improved IMODE, called IMODEII, is introduced. In IMODEII, Reinforcement Learning (RL), a computational methodology that simulates...Show More
A Review on Swarm Intelligence and Evolutionary Algorithms for Solving the Traffic Signal Control Problem
Palwasha W. Shaikh;Mohammed El-Abd;Mounib Khanafer;Kaizhou Gao
The rapid development of urban cities coupled with the rise in population has led to an exponentially growing number of vehicles on the roads for the latter to commute. This is adding to the already overbearing problem of traffic congestion. Short term, costly and short-sighted solutions of road infrastructure expansions are no longer suitable. One effective method of road resource allocation is f...Show More
Island-based Modified Harmony Search Algorithm with Neighboring Heuristics Methods for Flow Shop Scheduling with Blocking
Iyad Abu Doush;Mohammed Azmi Al-Betar;Mohammed A. Awadallah;Abdelaziz I. Hammouri;Mohammed El-Abd
2020 IEEE Symposium Series on Computational Intelligence (SSCI)
Year: 2020 | Conference Paper |
Cited by: Papers (1)
The flow shop scheduling with blocking involves assigning several jobs to machines with minimum time complexity. This problem can be considered as a combinatorial optimization problem that does not have an algorithmic solution. Recently, the modified harmony search algorithm with neighboring heuristics methods (MHSNH) is proposed to tackle this problem. In this paper, the flow shop scheduling with...Show More
Overall Optimization of Smart City by Multi-population Global-best Brain Storm Optimization using Cooperative Coevolution
Miao Zheng;Yoshikazu Fukuyama;Mohammed El-Abd;Tatsuya Iizaka;Tetsuro Matsui
2020 IEEE Congress on Evolutionary Computation (CEC)
Year: 2020 | Conference Paper |
Cited by: Papers (1)
This paper proposes a method for the overall optimization of smart city (SC). The proposed method is based on multi-population global-best brain storm optimization using cooperative coevolution (MP-CCGBSO). Using a SC model, energy cost, actual power loads during peak periods, and carbon dioxide emission can be minimized. For the SC problem, many researchers have proposed various evolutionary algo...Show More
Parameters Identification of Photovoltaic Cell and Module Using LSHADE
2020 12th International Conference on Advanced Computational Intelligence (ICACI)
Year: 2020 | Conference Paper |
Identifying circuit model parameters for photovoltaic cell and module is a challenging issue that often translates into an optimization problem. Recently, the most mainstream solution to such problems is based on metaheuristic optimization algorithms. Although there are many metaheuristic algorithms for the problem, the obtained parameters are often not very accurate and reliable. Therefore, a lin...Show More
Stimulating Research Projects Through Teaching a Course on the Internet of Things
2020 IEEE Global Engineering Education Conference (EDUCON)
Year: 2020 | Conference Paper |
Cited by: Papers (2)
The concept of the Internet of Things (IoT) refers to an emerging paradigm in which objects (things), that are not necessarily intelligent or traditionally part of the Internet, become highly connected and integrated in the Internet. With the appropriate sensor platform and actuators, these objects become constituents of intelligent IoT devices that collect a massive amount of data from the surrou...Show More
V-LAB – The Virtual Electric Machines Laboratory
Batool Hasan;Yara Al-Quorashy;Shahad Al-Mousa;Yousef Al-Sahhaf;Mohammed El-Abd
2020 IEEE Global Engineering Education Conference (EDUCON)
Year: 2020 | Conference Paper |
Cited by: Papers (11)
Virtual Reality (VR) is the current technology wave owing to its multi-disciplinary platform involving 3D modelling and visualization tools. Creating an Electric Machines laboratory with the use of Oculus Rift, Unity3D, and Leap Motion allows students to practice Electric Machines laboratory experiments in a safe environment, helping them gain a deeper understanding of how advanced engineering too...Show More
Cooperative Co-evolutionary Metaheuristics for Solving Large-Scale TSP Art Project
Junfeng Chen;Yuhao Wang;Xingsi Xue;Shi Cheng;Mohammed El-Abd
2019 IEEE Symposium Series on Computational Intelligence (SSCI)
Year: 2019 | Conference Paper |
Cited by: Papers (6)
As the amount and scale of cities in Traveling Salesman Problem (TSP) rise, the algorithmic complexity is exponentially increasing. The difficulty is how to design a suitable algorithm to solve large-scale TSPs. A Cooperative Co-evolutionary Ant Colony Optimization algorithm (CC-ACO) is proposed in this paper based on the concept of divide and conquer. The Iterative Self-Organizing Data Analysis (...Show More
Improved Moth-Flame Optimization Based on Opposition-Based Learning for Feature Selection
2019 IEEE Symposium Series on Computational Intelligence (SSCI)
Year: 2019 | Conference Paper |
Cited by: Papers (1)
In this paper, an improvement for the Moth-flame Optimization (MFO) algorithm is proposed based on Opposition-Based Learning (OBL), that enhances the exploration of the search space through computing the opposition values of solutions generated by MFO. Moreover, such an approach increases the efficiency of MFO as multiple regions in the search space are investigated at the same time. The proposed ...Show More
Gaussian Bare-Bones Brain Storm Optimization Algorithm
2019 IEEE Congress on Evolutionary Computation (CEC)
Year: 2019 | Conference Paper |
Cited by: Papers (2)
Brain Storm Optimization (BSO) is a population-based algorithm developed based on the humans brainstorming process. It has been successfully applied to many applications in the domain of non-linear continuous optimization. The performance of BSO has been enhanced in the literature through many works attempting to improve its different stages. In this work, we propose a Gaussian Bare-Bones version ...Show More
Total Optimization of Energy Networks in Smart City by Cooperative Coevolution using Global-best Brain Storm Optimization
Mayuko Sato;Yoshikazu Fukuyama;Mohammed El-Abd;Tatsuya Iizaka;Tetsuro Matsui
2019 IEEE Congress on Evolutionary Computation (CEC)
Year: 2019 | Conference Paper |
Cited by: Papers (4)
This paper proposes total optimization of energy networks in a smart city (SC) by cooperative coevolution using global-best brain storm optimization (CCGBSO). The smart city problem is one of mixed integer nonlinear programming (MINLP) problems. Therefore, various evolutionary computation methods such as differential evolutionary particle swarm optimization (DEEPSO), Brain Storm Optimization (BSO)...Show More
Improving SHADE with Center-based Mutation for Large-scale Optimization
2019 IEEE Congress on Evolutionary Computation (CEC)
Year: 2019 | Conference Paper |
Cited by: Papers (9)
Differential Evolution is a powerful and efficient approach for numerical optimization. A Success-History Based Parameter Adaptation (SHADE) is the recent variant of the adaptive DE that utilizes a historical performance of the successful control parameter. In this paper, we propose a center-based mutation for SHADE algorithm (CSHADE). In this mutation scheme, the base vector for SHADE's mutation ...Show More
Guidelines for Teaching an Introductory Course on the Internet of Things
2019 IEEE Global Engineering Education Conference (EDUCON)
Year: 2019 | Conference Paper |
Cited by: Papers (12)
The Internet of Things (IoT) is a concept coined after recent important developments in various research areas, especially wireless sensor networks. IoT refers to a new paradigm of the Internet in which various objects (or things), that were not traditionally part of the conventional Internet, attain the ability of being effective parts of communications networks. These things can actively collect...Show More
Balancing low-level vs. high-level programming knowledge in an undergraduate microprocessors course
2018 IEEE Global Engineering Education Conference (EDUCON)
Year: 2018 | Conference Paper |
Cited by: Papers (1)
In this work, we address the issue of balancing low-level vs. high-level programming knowledge and experience in embedded systems courses. On one hand, low-level programming (i.e. Assembly) is important for the students to fully understand how the machine works and have full control over its different capabilities and hardware features. On the other hand, high-level programming experience (i.e. C/...Show More
Medical Drones System for Amusement Parks
Ahmed Bitar;Aliaa Jamal;Hesham Sultan;Nour Alkandari;Mohammed El-Abd
2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA)
Year: 2017 | Conference Paper |
Cited by: Papers (13)
With the fast development of technology, many technological and industrial companies are working on coping with this growth. Therefore, various devices are being manufactured to be compatible with users. The main interest here is drones (flight controllers). As we can see nowadays, drones have many incredible uses for the future and they will soon revolutionize the entire industries. Drones are ne...Show More
RoadEye — The Intelligent Transportation System
2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA)
Year: 2017 | Conference Paper |
RoadEye is an intelligent transportation system project that will solve many traffic problems and make traffic safer. RoadEye is a system that will be able to detect weather conditions, maintain a safe distance and fixed speeds between vehicles. The proposed project implements a vehicle-to-vehicle-to-infrastructure system. The current system two features: Platooning for the vehicle-to-vehicle comm...Show More
A cooperative co-evolutionary LSHADE algorithm for large-scale global optimization
2017 IEEE Symposium Series on Computational Intelligence (SSCI)
Year: 2017 | Conference Paper |
Cited by: Papers (1)
In this paper, we propose the application of a Cooperative Co-evolutionary LSHADE (CCLSHADE) algorithm for Large-Scale Global Optimization (LSGO). We illustrate that by tuning two simple parameters of the CC framework, one can obtain very competitive results. The results are achieved without the need of incorporating local search modules, a re-initialization step, or adaptively configuring the CC ...Show More
Semi-autonomous indoor firefighting UAV
Abeer Imdoukh;Ahmed Shaker;Aya Al-Toukhy;Darin Kablaoui;Mohammed El-Abd
2017 18th International Conference on Advanced Robotics (ICAR)
Year: 2017 | Conference Paper |
Cited by: Papers (28)
Fire is one of the critical problems that have not been solved yet despite the technological development. Human losses are the most important aspect related to fires. Since it may be impossible to prevent fire from occurring, it would be helpful to minimize its impact in terms of human losses. The fact that unmanned aerial vehicles (UAVs) can handle dangerous and risky tasks as well as their fast ...Show More
A cherry-tomato harvesting robot
Fatemah Taqi;Fatima Al-Langawi;Heba Abdulraheem;Mohammed El-Abd
2017 18th International Conference on Advanced Robotics (ICAR)
Year: 2017 | Conference Paper |
Cited by: Papers (25)
The harvesting robot is a robot that is created for harvesting cherry tomatoes in households and greenhouses. For households, the project aims to protect the privacy of people who have their own gardens at home, and do not prefer to have workers coming to their home gardens to harvest the fruits. In addition, the weather in Kuwait is very hot, which makes it difficult for harvesters to work for lo...Show More
Cooperative coevolution using the Brain Storm Optimization Algorithm
2016 IEEE Symposium Series on Computational Intelligence (SSCI)
Year: 2016 | Conference Paper |
Cited by: Papers (7)
The Brain Storm Optimization (BSO) algorithm is a powerful optimization approach that has been proposed in the past few years. A number of improvements have been previously proposed for BSO with successful application for real-world problems. In this paper, the implementation of a Cooperative Co-evolutionary BSO (CCBSO) algorithm that is based on the explicit space decomposition approach is invest...Show More
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