113 research outputs found
Interview with Sanaa Gamil
No full textمقابلة مع الفنانة المصرية سناء جميل تناقش فيها فيلمها "توحيد" الحاصل على جائزة في الآونة الأخيرة، ورغبتها في لعب أدوار أنثوية جديدة تعكس تعقيداتها الزمنية. تتحدث أيضاًً عن اعتمادها على وعي الجمهور بجودة الفن. قامت بالمقابلة ليلى محمود.An interview with Egyptian actress Sanaa Gamil, in which she discusses her award-winning film "Tawheda," and her desire to play new feminine roles that reflect the time's complexities. The interview was conducted by Laila Mahmoud
IoD swarms collision avoidance via improved particle swarm optimization
No full textDrones flights have been investigated widely. In the presence of high density and complex missions, collision avoidance among swarm of drones and with environment obstacles becomes a challenging task and indispensable. This paper aims to enhance the optimality and rapidity of three dimensional IoD path generation by improving the particle swarm optimization (PSO) algorithm. The improvements include using chaos map logic to initialize the population of PSO. Also, adaptive mutation is utilized to balance local and global search. Then, the inactive particles are replaced by new fresh particles to push the solution toward global optimal. Furthermore, Monte Carlo simulation is carried out and the results are compared with slandered PSO and with recent work CIPSO. The results exhibit significant improvement in convergence speed as well as optimal solution which prove the ability of proposed method to generate safety path for IoD formation without collision with terrain obstacle and among drones.The authors would like to acknowledge the support of the department of the computer engineering at King Fahd University of Petroleum and Minerals for this work.Ahmed, G (corresponding author), King Fahd Univ Petr & Minerals, Comp Engn Dept, Dhahran, Saudi Arabia.
[email protected]; [email protected]; [email protected]; [email protected]
Energy-Efficient UAVs Coverage Path Planning Approach
No full textUnmanned aerial vehicles (UAVs), commonly known as drones, have drawn significant consideration thanks to their agility, mobility, and flexibility features. They play a crucial role in modern reconnaissance, inspection, intelligence, and surveillance missions. Coverage path planning (CPP) which is one of the crucial aspects that determines an intelligent system's quality seeks an optimal trajectory to fully cover the region of interest (ROI). However, the flight time of the UAV is limited due to a battery limitation and may not cover the whole region, especially in large region. Therefore, energy consumption is one of the most challenging issues that need to be optimized. In this paper, we propose an energy-efficient coverage path planning algorithm to solve the CPP problem. The objective is to generate a collision-free coverage path that minimizes the overall energy consumption and guarantees covering the whole region. To do so, the flight path is optimized and the number of turns is reduced to minimize the energy consumption. The proposed approach first decomposes the ROI into a set of cells depending on a UAV camera footprint. Then, the coverage path planning problem is formulated, where the exact solution is determined using the CPLEX solver. For small-scale problems, the CPLEX shows a better solution in a reasonable time. However, the CPLEX solver fails to generate the solution within a reasonable time for large-scale problems. Thus, to solve the model for large-scale problems, simulated annealing for CPP is developed. The results show that heuristic approaches yield a better solution for large-scale problems within a much shorter execution time than the CPLEX solver. Finally, we compare the simulated annealing against the greedy algorithm. The results show that simulated annealing outperforms the greedy algorithm in generating better solution quality.This research was funded by Project Number INML2104 under the InterdisciPlinary Center of Smart Mobility and Logistics, KFUPM.
The authors would like to acknowledge the support of the Interdisciplinary Center of Smart Mobility and Logistics, and the Department of Computer Engineering at King Fahd University of Petroleum and Minerals for the support of this research
3D simulation model for IoD-to-vehicles communication in IoD-assisted VANET
No full textVehicle ad hoc networks (VANETs) have gradually emerged to enhance transportation information, entertainment, safety, and other services. However, such infrastructures have certain limitations, causing intermittent network disconnection. Further, in urban areas, terrain heights act as obstacles and hinder or attenuate transmitted signals. In this study, we propose a dynamic 3D internet of drones collaborative communication approach for efficient VANET-assistance (3DIoDAV) by integrating the IoD network and VANET to support terrestrial communication. We model IoD locations as an optimization problem to optimize the IoD nodes in three-dimensional terrain. Improved particle swarm optimization is used to optimally deploy IoD nodes in 3D terrain for minimizing the number of isolated vehicles. The proposed approach considers the terrain profile influence on communication. Therefore, we propose a 3D propagation model for efficient IoD-to-vehicle (IoD2V) communication in 3D space. Experiments are performed based on the received signal from ground vehicles to examine the performance of the proposed model and the 3DIoDAV approach. Simulation results show different behaviors of IoD nodes in two-dimensional (2D) and 3D scenarios. Comparison with 2D VANET-assisted and IoDAV approaches demonstrates the proposed 3DIoDAV approach's ability to detect terrain obstacles, which guarantees the dispatching of IoD nodes into the most appropriate locations in 3D space, thereby minimizing the impact of terrain obstacles on communication.The authors declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by (the interdisciplinary center of smart mobility and
logistics at King Fahd University of Petroleum and Minerals) [Grant number (INML2033)]. This study was also supported by the Special Research Fund (BOF) number BOF23KV17.
The authors acknowledge the support project number INML2104 under the interdisciplinary center of smart mobility and logistics and the computer engineering department at King Fahd University of Petroleum and Minerals for this study
An Optimization Approach of IoD Deployment for Optimal Coverage Based on Radio Frequency Model
No full textRecently, Internet of Drones (IoD) has garnered significant attention due to its widespread applications. However, deploying IoD for area coverage poses numerous limitations and challenges. These include interference between neighboring drones, the need for directional antennas, and altitude restrictions for drones. These challenges necessitate the development of efficient solutions. This research paper presents a cooperative decision-making approach for an efficient IoD deployment to address these challenges effectively. The primary objective of this study is to achieve an efficient IoD deployment strategy that maximizes the coverage region while minimizing interference between neighboring drones. In deployment problem, the interference increases as the number of deployed drones increases, resulting in bad quality of communication. On the other hand, deploying a few drones cannot satisfy the coverage demand. To accomplish this, an enhanced version of a concise population-based meta-heuristic algorithm, namely Improved Particle Swarm Optimization (IPSO), is applied. The objective function of IPSO is defined based on the coverage probability, which is primarily influenced by the characteristics of the antennas and drone altitude. A radio frequency (RF) model is derived to evaluate the coverage quality, considering both Line of Sight (LOS) and Non-Line of Sight (NLOS) down-link coverage probabilities for ground communication. It is assumed that each drone is equipped with a directional antenna to optimize coverage in a given region. Extensive simulations are conducted to assess the effectiveness of the proposed approach. Results demonstrate that the proposed method achieves maximum coverage with minimum transmission power. Furthermore, a comparison is made against Collaborative Visual Area Coverage Approach (CVACA), and a game-based approach in terms of coverage quality and convergence speed. The simulation results reveal that our approach outperforms both CVACA and the gamebased schemes in terms of coverage and convergence speed. Comparisons validate the superiority of our approach over existing methods. To assess the robustness of the proposed RF model, we have considered two distinct ranges of noise: range1 spanning from -120 to -90 dBm, and range2 spanning from -90 to -70 dBm for different numbers of UAVs. In summary, this research presents a cooperative decision-making approach for efficient IoD deployment to address the challenges associated with area coverage and achieves an optimal coverage with minimal interference.This research was funded by Project Number INML2104 under the Interdisciplinary Center of Smart Mobility and Logistics at King Fahd University of Petroleum and Minerals. This study also was supported by the Special Research Fund BOF23KV17.
Authors at KFUPM would like to acknowledge the support received under University Funded Grant # INML2300. The author at Hasselt University acknowledges the support received from Special Research Fund (BOF) under Grant # BOF23KV17
Energy-Efficient Internet of Drones Path-Planning Study Using Meta-Heuristic Algorithms
No full textThe increasing popularity of unmanned aerial vehicles (UAVs), commonly known as drones, in various fields is primarily due to their agility, quick deployment, flexibility, and excellent mobility. Particularly, the Internet of Drones (IoD)-a networked UAV system-has gained broad-spectrum attention for its potential applications. However, threat-prone environments, characterized by obstacles, pose a challenge to the safety of drones. One of the key challenges in IoD formation is path planning, which involves determining optimal paths for all UAVs while avoiding obstacles and other constraints. Limited battery life is another challenge that limits the operation time of UAVs. To address these issues, drones require efficient collision avoidance and energy-efficient strategies for effective path planning. This study focuses on using meta-heuristic algorithms, recognized for their robust global optimization capabilities, to solve the UAV path-planning problem. We model the path-planning problem as an optimization problem that aims to minimize energy consumption while considering the threats posed by obstacles. Through extensive simulations, this research compares the effectiveness of particle swarm optimization (PSO), improved PSO (IPSO), comprehensively improved PSO (CIPSO), the artificial bee colony (ABC), and the genetic algorithm (GA) in optimizing the IoD's path planning in obstacle-dense environments. Different performance metrics have been considered, such as path optimality, energy consumption, straight line rate (SLR), and relative percentage deviation (RPD). Moreover, a nondeterministic test is applied, and a one-way ANOVA test is obtained to validate the results for different algorithms. Results indicate IPSO's superior performance in terms of IoD formation stability, convergence speed, and path length efficiency, albeit with a longer run time compared to PSO and ABC.The authors would like to acknowledge the support of the Computer Engineering Department at King Fahd University of Petroleum and Minerals for the support of this work
UA-R-GC-1914-01-01-1967-01-05_Page-010
No full textI - 10 -
**Baracat Zaki Cohen+ Mahmoud Said El Derini
*Claude Jean Artinian+ Mohamed Salam Shurrab
Esam Bahig Kronfli Nabil I. Marzouk
***Haagop Krikor Spendjian *Shahira Gamil Mehrez
Hassan Hany Afifi+ Wahib Girgis Abiskhairon
Yahia Ahmed Moustapha EI Koragaty
BACHELOR OF ARTS
From the Undergraduate Faculty of Arts & Sciences
English Literature
Iro Platon Valaskaki
Marianne Homere Avierino
***Nihad Ahmed Salem
Economics
Edgar Botros Tawfik
Heba Ahmed Handoussa (In
absentia) +
Herman Friedrich Kroeger
Economics-Political Science
**Rafida Ahmed Shukairy (In absentia)
Saneya Shaarawi Lanfranchi+
Thalia Tectonidis+
Hoda Hamed Mohamed
Hussein Ahmed Enan
Mazen Wasfi Abdul Majeed
Mohamed Hosny Afifi (In absentia) +
Adil Mohamad Zulificar *Ilham Moyine AI-Arab
Ahmed Farid Abdel Hamid Assali Issa Zaki Dajani+
Amira Hanna Mishriky Jean-Claude Sakellarios (In absentia)
Amira Hassan Bassiouni+ John Andrew Zillis
**Arlette Daniel Klein+ **Magda Fathi El Saifi
Atef Zaki Bassiony Nasr *Misliar Rachid Hussein
Dalia Mohy Eldin Abdin+ Mohamed Abu Bakr EI Missiri
Eleonore Edouard Fernandez Mohamed Farouk Abd EI Hamid EI
Fatma EI-Zahraa Hassan Barrada Assali (In absentia) +
George Ivanov Kalushev (In Mona Tewfik Mirshak
absentia) Mounira Fahim Isaac+
**Germaine Michel Gibara Paulette Gabriel Karout+
Hamazasb Artinian (In absentia)+ Samuel Nyamai Ndemange
Heddy Mohammed Shedid **Sana Mahmoud Hassan
Heidemarie Bochow Soad Abdel Hamid Hashem+
Hend Magdi EI Sayed Soha Mohamed Zaki Abdel Kader
Hoda Aly Serour Zuheir Atta Farah (In absentia) +
Sociology-AnthropologX
#Alexandra John Parikakis
**Amina Abdel Wahab
Amira Raja Hassan Dajani
Azza Sabet+
Carmen Adly Boutros+
Christiane Maurice Tewfik
Geargeoura
Giovanna Paola Barbieri (In absentia)
Gumushe Gamil Assem /+
Hanan Emil Talhamy
Lucy Diran Gureghian
Sawasn Mahmoud El Missiri
Sherif Mahmoud El Hakee
Pharmaceutical procurement practice aspects
No full textProcurement is the most important part of the pharmaceutical logistic cycle. It is the process of acquiring supplies after a properly selected list of products. The procurement system or model depends on the type of organization weather it is governmental or private, centralized or decentralized, autonomous or semiautonomous. The objectives of procurement system is to make available the right drug in an appropriate quantities of adequate quality from a reliable supplier at the right time with the lowest possible prices through an ethical and legal procedures. Prequalification of suppliers is the successful quality assurance activity. Needs and funds can be reconciled and a rational cut can be done by using ABC- VAN matrix technique. Purchasing should be by transparent competition through open tender, restrictive tender, restricted competition or in certain cases by direct negotiation by transparent committee leading to transparent contract. One of the most important procurement practice for the system to succeed is the reliable payment and efficient financial management and monitoring the supplier performance. The system should have an efficient quality assurance program with annual auditing and regular reports
Risk factors for Alzheimer's disease: An autopsy-based case-control study.
No full textThe study of the relationship between premorbid brain weight and Alzheimer's disease has not been addressed before. This important epidemiological research question is mainly ignored because of the lack of quantitative measures of premorbid brain weight or its equivalent. This autopsy-confirmed case-control study was conducted from April 1992 to October 1994. The autopsy-based design generated and enabled testing of such a new and biologically plausible hypothesis of low premorbid brain weight and increased risk for AD. In addition, the design permitted the examination of other potential risks proposed in the literature including sociodemographic, familial, medical, psychological and life style factors. The study included 212 subjects in the final analysis (119 AD cases and 93 normal controls), from both genders (148 males and 64 females), and from both races (204 whites and 8 blacks). Study subjects were drawn from the Michigan Alzheimer's Disease Research Center (MADRC) database and the University of Michigan Hospitals autopsy pool. The adjusted odds ratios (ORS) indicated statistically significant positive associations for family history of AD and other dementias past history of epilepsy, past history of depression and use of antidepressants and history of severe head injury. To the contrary, the ORs for use of antiinflammatory drugs (steroidal and non-steroidal) and for lifetime exposure for cigarette smoking showed a statistically significant inverse associations with AD suggesting a potential protective effect. Low educational level, lifetime exposure for alcohol, past histories of hypothyroidism, peptic ulcer, diabetes and antecedent surgical procedures were not associated with AD. The hypothesis of low brain weight as a risk factor for AD was examined. Differences between the mean brain weights of cases and controls were statistically significant. Brain weight was categorized into two groups small vs large, using a cut point of 1100 grams, and the association was examined. There was a significant inverse association between brain weight and risk for AD. Multiple linear regression models were examined to determine brain weight best predictors at autopsy. Then, the association between brain weight and AD, with brain weight and its predictors in the model, was examined using logistic regression. The association remained statistically significant even after controlling for the degree of brain atrophy, and brain weight emerged as an independently significant predictor of the risk for AD. (Abstract shortened by UMI.)PhDHealth and Environmental SciencesMental healthPublic healthUniversity of Michigan, Horace H. Rackham School of Graduate Studies, School of Public Healthhttp://deepblue.lib.umich.edu/bitstream/2027.42/129584/2/9542209.pd
GOVERNANCE OF MASS DISPLACEMENT IN THE MIDDLE EAST: LEBANON AND JORDAN IN COMPARATIVE PERSPECTIVE
No full textPh.DDOCTOR OF PHILOSOPHY (SPP
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