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  • Publication
    Optimizing Aircraft Pitch Control Systems: A Novel Approach Integrating Artificial Rabbits Optimizer with PID-F Controller
    (2024)
    Abualigah, Laith
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    Izci, Davut
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    Ekinci, Serdar
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    The precise control of aircraft pitch angles is critical in aviation for maintaining specific attitudes during flight, including straight and level flight, ascents, and descents. Traditional control strategies face challenges due to the non-linear and uncertain dynamics of flight. To address these issues, this study introduces a novel approach employing the artificial rabbits optimizer (ARO) for tuning a PID controller with a filtering mechanism (PID-F) in aircraft pitch control systems. This combination aims to enhance the stability and performance of the aircraft pitch control system by effectively mitigating the kick effect through the incorporation of a filter coefficient in the derivative gain. The study employs a time-domain-based objective function to guide the optimization process. Simulation results validate the stability and consistency of the proposed ARO/PID-F approach. Comparative analysis with various optimization algorithm-based controllers from the literature demonstrates the effectiveness of the proposed technique. Specifically, the ARO/PID-F controller exhibits a rapid response, zero overshoot, minimal settling time, and precise control during critical phases. The obtained results position the proposed methodology as a promising and innovative solution for optimizing aircraft pitch control systems, offering improved performance and reliability.
      5
  • Publication
    Heavy metal and soluble organic matter removal using natural conglomerate and siltstone soils: Towards soil aquifer treatment for oily wastewater
    (2024)
    Ali, Jisha Kuttiani
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    Ghaleb, Hala
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    Arangadi, Abdul Fahim
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    Pham Le, Tu Phuong
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    Stephen, Sasi
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    Jouini, Mohamed Soufiane
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    Moraetis, Daniel
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    Alhseinat, Emad
    The present work aims to assess the viability of vadose zone siltstone and conglomerate for oil and gas-produced water (PW) treatment using soil aquifer treatment (SAT). Comprehensive batch adsorption tests were carried out to analyze siltstone and conglomerate removal capacity for dissolved organics (phenol), and heavy metal ions (Ni 2+, and Zn 2+). The results demonstrated that conglomerate displayed a 98% removal capacity for Zn 2+ and 88% for Ni2+ while siltstone showed 82% removal for Zn2+ and 88% removal for Ni 2+. However, both siltstone and conglomerate showed low phenol removal (32% for siltstone, and 9% for conglomerate). The equilibrium adsorption isotherms were fitted by several adsorption models. The Langmuir model exhibited the best fitting for the adsorptions of phenol, Ni 2+ ions, and Zn 2+ ions on the two soils. The kinetics studies have revealed that phenol, Ni 2+ ions, and Zn 2+ ions adsorption on the two soil samples obey a pseudo-second-order kinetic model. Furthermore, Fourier transform infrared spectroscopy studies revealed that the Si-O peak in the soil plays a predominant role in interactions with heavy metal ions and phenol due to its high content in the soils. However, the electrostatic interactions between functional groups (Si-O, CO32-, and Cdouble bondO carbonyl groups) of the soil samples and the Ni2+ ions, Zn2+ ions, and phenol also contributed to the removal capacity. It is revealed that Zn2+ has a greater affinity for carboxyl groups than Ni2+. The obtained data in this study would support the effective design of SAT treatment for PW and help in reducing the risk of contaminating the groundwater aquifer.
      3
  • Publication
    “Arabic Pop Art” on Instagram: Questioning the Representations of Arabness and Khaleejiness in Digital Art
    Instagram, the second most widely used social networking platforms in the world, is a privileged place for artists and art lovers to showcase artworks and visual content to a larger audience. In the Middle East and North Africa region, one Instagram account, @arabic.pop.art, currently gathers 399,000 followers by reposting daily various forms of digital work produced in the region. Based on the analysis of all the posts published there from March 2019 to March 2020, I discuss the important presence of Gulf citizens and residents among both the artists and the followers of this Instagram account and how Arab and gulfic/khaleeji symbols, icons and consumerist items are being used in the published artworks. Through its content and given its popularity, this account is actively participating in highlighting Arab youth pop culture and shaping representations of Arab and regional identities (Arabness and Khaleejiness).
      1
  • Publication
    An investigation to identify the factors that cause failure in English essay, precis, and composition papers in CSS exams
    (2024)
    Gul, Kiran
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    Shahzad, Waheed
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    Raza, Ali
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    Hanandeh, Essam
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    Aldiabat, Khaled
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    Shboul, Rabah
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    Abualigah, Laith
    The research study aims to examine why candidates in Pakistan failed the English Essay, Precis, and Composition sections of the Central Superior Services (CSS) tests. Those candidates chosen for various civil service positions take the prestigious and difficult CSS exam. The study aims to discover candidates’ difficulties in these particular CSS exam sections and investigate methods for enhancing their English language ability. A mixed-methods strategy is used in the research process to collect both quantitative and qualitative data. Participants in the CSS exam who once took the English Essay, Precis, and Composition papers and got fail in it received a survey form to respond according to their experience. Other than this, we also conducted semi-structured interviews with CSS test winners currently working as officials, such as Deputy Commissioners, Assistant Commissioners, Assistant Superintendents of Police, and Deputy Superintendents of Police. Insights into the causes of failure and the experiences of successful candidates are sought after from both data sources. The research findings highlighted several key factors contributing to failure in English Essays, Precis, and Composition papers. These factors include lack of comprehension and understanding, grammatical errors, inadequate organization, poor handwriting, insufficient practice, lack of originality, difficulty in adapting to essay prompts and precis passages, poor organization, failure to understand and address the purpose, insufficient development of ideas, failure to reach the required word count, grammatical mistakes, neglecting proofreading and revision, poor writing expression, and weak induction and conclusion in essays, tough paper pattern old formatted curriculum. Participants reported struggling to express their ideas coherently, having limited language skills, facing challenges in managing time effectively, lacking proper precis structure understanding, inadequate expertise in the subject, lack of training and resources, lack of analytical and critical thinking abilities, inadequate exam preparation, time management issues, poor grammar abilities, exam phobia, and limited vocabulary as potential factors contributing to failure.
  • Publication
    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization
    (2024) ; ;
    Abualigah, Laith
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    Barbaresco, Frederic
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    Seghrouchni, Amal ElFallah
    This paper presents a novel hybrid optimization method to solve the resource allocation problem for multi-target multi-sensor tracking of drones. This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. The goal is to select a set of sensors based on norms of weighted distances cost function. The norms are the Euclidean distance and the Mahalanobis distance between the drone location and the sensors. The second one depends on the predicted covariance of the tracker. The Extended Kalman Filter (EKF) is used for state estimation with proper clutter and detection models. Since we use Multi-objects to track, the Joint Probability Distribution Function (JPDA) estimates the best measurement values with a preset gating threshold. The goal is to find a sensor or minimum set of sensors that would be enough to generate high-quality tracking based on optimum resource allocation. In the experimentation simulated with Stone Soup, one radar among five radars is selected at every time step of 50-time steps for 200 tracks distributed over 20 different ground truths. The proposed IPDOA provided optimum solutions for this complex problem. The obtained solution is an optimum offline solution that is used to select one or more sensors for any future flights within the vicinity of the 5 radars. Environment and conditions are assumed to be similar in future drone flights within the radars’ defined zone. The IPDOA performance was compared with the other 8 metaheuristic optimization algorithms and the testing showed its superiority over those techniques for solving this complex problem. The proposed simulated model can find the most relevant sensor(s) capable of generating the best quality tracks based on weighted distance criteria (Euclidean and Mahalanobis ). That would cut down the cost of operating extra sensors and then it would be possible to move them to other vicinity.