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Upgrading Sustainability in Clean Energy: Optimization for Proton Exchange Membrane Fuel Cells Using Heterogeneous Comprehensive Learning Bald Eagle Search Algorithm
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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).

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Effect of Operating Conditions on Reverse Osmosis (RO) Membrane Performance
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The aim of this research is to study the effect of high concentrations of salts, pressure and temperature on the performance of the RO membrane with time. Four different (Na2CO3) concentrations (5000, 15000, 25000 and 35000) ppm and various pressures such as (1, 3 and 5) bars at different temperatures of the feed solution (i.e., 25, 35 and 45) ◦C were used in this work. It was found that, as the concentration of salt and feed temperatures increase, the rejection of the salt decrease. While the salt rejection of the membranes increases with increase of transmembrane pressure.

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Publication Date
Thu Dec 31 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The contribution of the Environmental Audit to achieving the Sustainability of the Environmental Balance in the Sudanese Business Environment
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This study tackles the contribution of the environmental audit in achieving the sustainability of the environmental balance in the Sudanese business environment. The study aimed at clarifying the role of environmental auditing in supporting sustainable development, and to recognize the role of environmental audit in urging businesses to abide by environmental protection. It also shows how effective the environmental audit reports are, in providing the reliable data for the concerned authorities, in order to use it in making the decisions that would help in the sustainability of the environmental balance. To achieve the goals of the study, a questionnaire was developed and distributed to the registered chartered accountants in Sud

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Publication Date
Wed Oct 11 2023
Journal Name
Journal Of Educational And Psychological Researches
The Relationship between Formal Thinking & Learning Styles for Kindergarten Department Students
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The current research aims to reveal the strength of education and the direction of the relationship between the formal thinking and learning methods of Kindergarten department students. To achieve this objective, the researcher developed a scale of formal thinking according to the theory of (Inhelder & Piaget 1958) consisting of (25) items in the form of declarative phrases derived from the analysis of formal thinking skills based on a professional situation that students are expected to interact with in a professional way. The research sample consisted of (100) female students selected randomly who were divided into four groups based on the academic stages, the results revealed that The level of formal thinking of the main sample is

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Publication Date
Tue Nov 01 2022
Journal Name
Optik
Design new D-π-A materials for sensitizers for dye-sensitized solar cells: Quantum chemical study
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Within this paper, we developed a new series of organic chromophores based on triphenyleamine (TPA) (AL1, AL-2, AL-11 and AL-22) by engineering the structure of the electron donor (D) unit via replacing a phenyle ring or inserting thiophene as a π-linkage. For the sake of scrutinizing the impact of the TPA donating ability and the spacer upon the photovoltaic, absorptional, energetic, and geometrical characteristic of these sensitizers, density functional theory (DFT) and time-dependent DFT (TD-DFT) have been utilized. According to structural characteristics, incorporating the acceptor, π-bridge and TPA does not result in a perfect coplanar conformation in AL-22. We computed EHOMO, ELUMO and bandgap (Eg) energies by performing frequency a

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Publication Date
Tue Sep 30 2025
Journal Name
Gsc Advanced Research And Reviews
A comprehensive review of metal-organic framework based biosensors for detection of reactive oxygen species and hydrogen peroxide in biomedical applications
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Metal-organic frameworks (MOFs) have emerged as revolutionary materials for developing advanced biosensors, especially for detecting reactive oxygen species (ROS) and hydrogen peroxide (H₂O₂) in biomedical applications. This comprehensive review explores the current state-of-the-art in MOF-based biosensors, covering fundamental principles, design strategies, performance features, and clinical uses. MOFs offer unique benefits, including exceptional porosity (up to 10,400 m²/g), tunable structures, biocompatibility, and natural enzyme-mimicking properties, making them ideal platforms for sensitive and selective detection of ROS and H₂O₂. Recent advances have shown significant improvements in detection capabilities, with limit

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Publication Date
Wed Apr 06 2022
Journal Name
Neuroquantology
Theoretical Study of Photons Spectra around High Energy of Quark-antiquark Using QCD Theory
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In this paper, we study and investigate the quark anti-quark interaction mechanism through the annihilation process. The production of photons in association with interaction quark and gluon in the annihilation process. We investigate the effect of critical temperature, strength coupling and photons energy in terms of the quantum chromodynamics model theory framework. We find that the use of large critical temperature Tc =134 allows us to dramatically increase the strength coupling of quarks interaction. Its sensitivity to decreasing in photons rate with respect to strength coupling estimates. We also discuss the effect of photons energy on the rate of the photon , such as energies in range (1.5 to 5 GeV).The photons rate increases

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Publication Date
Wed Jun 30 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Promising Gains of 5G Networks with Enhancing Energy Efficiency Using Improved Linear Precoding Schemes
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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Toxicity Reduction of Reactive Red Dye-238 Using Advanced Oxidation Process by Solar Energy
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Decolorization of red azo dye (Cibacron Red FN-R) from synthetic wastewater has been investigated as a function of solar advanced oxidation process. The photocatalytic activity using ZnO as a photocatalysis has been estimated. Different parameters affected the removal efficiency, including pH of the solution, initial dye concentration and H2O2 concentration were evaluated to find out the optimum value of these parameters. The results proved that the optimal pH value was 8 and the most efficient H2O2 concentration was 100mg/L. Toxicity reduction percent for effluent solution was also monitored to assess the degradation process. This treatment method was able to strongly reduce the color and toxicity of reactive red dye-238 to about (99 an

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Publication Date
Wed May 03 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Enhancing smart home energy efficiency through accurate load prediction using deep convolutional neural networks
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The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

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