Clean energy applications widely recognize Proton Exchange Membrane Fuel Cells (PEMFCs) for their high efficiency and environmental compatibility. Accurate parameter identification of PEMFC models is essential for enhancing system performance and reliability, particularly under dynamic operating conditions. This paper presents a novel optimization-based approach called Heterogeneous Comprehensive Learning-Bald Eagle Search (HCLBES) with enhanced exploration and exploitation capabilities for the effective modeling of PEMFC. The algorithm combines the exploration strength of the Bald Eagle Search with comprehensive learning and heterogeneity mechanisms to achieve a balanced global and local search space. In this algorithm, the number of agents is divided into two subagents. Each subagent is assigned to focus solely on either exploration or exploitation. The comprehensive learning strategy generates exemplars for both subgroups. In the exploration sub-agent, exemplars are generated using the personal best experiences of agents within that same exploration space. The exploitation subagent generates the exemplars using the personal best experiences of all agents. This separation preserves exploration diversity even if exploitation converges prematurely. The algorithm is applied to optimize parameters of the 250 W and 500 W PEMFC models under varying conditions. Simulation results demonstrate the outperformance of the HCLBES algorithm in terms of convergence speed, estimation accuracy, and robustness compared to recent optimization algorithms. The effectiveness of HCLBES was also verified through statistical metrics and different commercial PEMFC models, including BCS 500 W stacks, Horizon 500, and NedStack PS6. Experimental validation confirms that the proposed algorithm effectively captures the nonlinear behaviours of PEMFCs under dynamic operating conditions. This research aligns with the Sustainable Development Goals (SDGs) by promoting clean and affordable energy (SDG 7) through the enhanced efficiency and reliability of PEMFCs, thereby supporting sustainable industrialization and innovation (SDG 9).
In many video and image processing applications, the frames are partitioned into blocks, which are extracted and processed sequentially. In this paper, we propose a fast algorithm for calculation of features of overlapping image blocks. We assume the features are projections of the block on separable 2D basis functions (usually orthogonal polynomials) where we benefit from the symmetry with respect to spatial variables. The main idea is based on a construction of auxiliary matrices that virtually extends the original image and makes it possible to avoid a time-consuming computation in loops. These matrices can be pre-calculated, stored and used repeatedly since they are independent of the image itself. We validated experimentally th
... Show MoreThe paper aims to measure the impact of monetary policy on price stability , by testing the causal relationship between the money supply, inflation rate and the exchange rate , In order to prove that the inflation is a monetary phenomenon in the Iraqi economy , and that the exchange rate is controlled in the money supply , the money supply as an endogenous variable continued we found by using the standard tests to the existence of a single co-integration between the money supply and the rate of inflation and the money supply and the parallel exchange rate, This confirms the existence of a long-term relationship between the variables , It also confirmed the results of the vector error correctio
... Show MoreThe environmental problems that have emerged recently as a result of pressure on the environment due to the increase in population size, especially in urban cities, where this increase was accompanied by the need for housing as well as the need for services and activities. This led to the establishment of many vertical residential buildings represented by residential complexes within the urban fabric of the city of Baghdad. As part of following the methodology of urban dictation policies in empty areas, and to accommodate the largest number of residents as a result of the multiplicity of floors and housing, these buildings must be subject to the standards and requirements of sustainability at the level of their spatial location and their
... Show MoreExcess heat significantly reduces the efficiency and lifespan of electrical and optoelectronic devices. While passive radiative cooling is becoming more common, achieving active thermal control without physical reconfiguration remains challenging. Unlike conventional static absorbers, we propose a broadband plasmonic solar absorber designed to regulate energy absorption in the near-infrared (NIR) region without modifying the geometrical parameters. The design utilizes a coaxial cylindrical metal-insulator-metal (MIM) configuration, combining refractory copper (Cu), silicon dioxide (SiO2), and a trilayer graphene (Gr) that allows electrical tuning in a broadband solar absorber. Simulation results show a maximum broadband absorption efficienc
... Show MoreAutism spectrum disorder(ASD) is a neurological condition marked by impaired communication abilities, social detachment, and repetitive behaviors in individuals. Global health organization facing difficulties in establishing an effective ASD diagnostic system that facilitates precise analysis and early autism prediction. It is a scientific issue that necessitates resolution. This research presents an approach for the early prediction of children with ASD utilizing significant variables through machine learning (ML) methods. Three stages comprise the suggested technique. First, a 1250-case ASD dataset was identified and preprocessed. Five extremely effective traits with high Pearson c
Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co
... Show MoreThe biometric-based keys generation represents the utilization of the extracted features from the human anatomical (physiological) traits like a fingerprint, retina, etc. or behavioral traits like a signature. The retina biometric has inherent robustness, therefore, it is capable of generating random keys with a higher security level compared to the other biometric traits. In this paper, an effective system to generate secure, robust and unique random keys based on retina features has been proposed for cryptographic applications. The retina features are extracted by using the algorithm of glowworm swarm optimization (GSO) that provides promising results through the experiments using the standard retina databases. Additionally, in order t
... Show MoreLight isotopes, especially closed shell nuclei, have significance in thermonuclear reactions of the Carbon-Nitrogen-Oxygen (CNO) cycle in stars. In this research, 12C(p, γ) 13N and 14N(p, γ) 15O reactions have been calculated by means of Matlab codes to find the reaction rate across a temperature range of 0.006 to 10 GK using non-resonant parts, as well as the astrophysical S- factor S(E) at low energies. It was concluded that the high binding energy of 12C and 14N nuclei make the reaction less probable thus enabling other competitive processes to develop, which enhances the probability of other competitive proton reactions in the CNO cycle.
We describe curved-mirror Fabry-Perot cavities with embedded silicon nitride membranes, fabricated using a monolithic surface-micromachining process. The presence of the suspended membranes was confirmed by confocal microscopy, and their properties were verified through optical studies and thermomechanical calibration of mechanical/vibrational noise spectra measured at room temperature and atmospheric pressure. The cavities exhibit reflectance-limited finesse (