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2nd International Conference on Energy Transition and Security, ICETS 2023

作者： Danoune, Mohammed Bilal Djafour, Ahmed Hamouda, Messaoud Degla, Aicha Gougui, Abdelmoumen Rehouma, Youssef Seddik, Zemitte Ahmed Draia University Sustainable Development and Computer Science Laboratory SDCS-L Adrar Algeria Université Kasdi Merbah Ouargla Faculté des Sciences Appliquées Laboratoire Lage Ouargla Algeria Centre de Dévelopment des Ener Gies Renotivelables -CDER Bouzareah Algeria

ISBN: (纸本)9798350372182

Hydrogen is an attractive fuel if it is produced from renewable energy sources (RES). The most ecological approache of green hydrogen generation, today, is the water electrolysis using RES. The present paper investigates the viability of hydrogen production from the solar energy resources of Adrar province (Lat: 27°52'N, Long: 0°17'W, Alt: 257m A.S.L) in Algeria using accurate monthly solar radiation mathematical model. Some of the key results exhibited that the daily average month solar energy varies from 3.93 Kwh to 8.79 Kwh in Adrar. Polycrystalline photovoltaic (PV) panel with 175 Wp rated power and proton exchange membrane (PEM) electrolyzer are employed. The required economic study is conducted to calculate the levelized cost of electricity (LCOE) and hydrogen (LCOH2). The final results reveal that the annual hydrogen production ranges between 3.06×105 and 6.77×105 Kg in 1 Km2 surface. Furthermore, cost of hydrogen production from solar resources in Adrar is competitive, where the price of 1 Kg of hydrogen is 3.51 $. © 2023 IEEE.

关键词： Economic analysis

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Potential and Economic Viability of Green Hydrogen Production by Water Electrolysis using Solar Energy in Oran, Algeria 2

Potential and Economic Viability of Green Hydrogen Productio...

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2nd International Conference on Energy Transition and Security, ICETS 2023

作者： Danoune, Mohammed Bilal Djafour, Ahmed Hasnaoui, Abir Hamouda, Messaoud Degla, Aicha Gougui, Abdelmoumen Rehouma, Youssef Seddik, Zemitte Ahmed Draia University Sustainable Development and Computer Science Laboratory SDCS-L Adrar Algeria Université Kasdi Merbah Ouargla Faculté des Sciences Appliquées Laboratoire Lage Ouargla Algeria University of Science and Technology of Oran Mohamed-Boudiaf Development of Electrotechnics Faculty of Electrical Engineering Oran31000 Algeria Centre de Dévelopment des Energies Renouvelables -CDER Algeria Bouzareah Algeria

ISBN: (纸本)9798350372182

The current study investigates the viability of hydrogen production from the solar energy resources of Oran province (Lat: 35°42'N, Long: 0°38'W) in Algeria using accurate monthly solar radiation mathematical model. Some of the key results exhibit that the monthly solar energy varies from 77.08 to 218.70 Kwh/m2/month in Oran. Polycrystalline photovoltaic (PV) panel with 175 Wp rated power and proton exchange membrane (PEM) electrolyzer are employed. In addition, an economic study using the levelized cost of electricity (LCOE) and hydrogen (LCOH2) is performed. The final results reveal that the annual hydrogen production ranges between 1.94×105 and 5.50×105 Kg in 1 Km2 surface. Furthermore, cost of hydrogen production from solar resources in Oran is competitive, where the price of 1 Kg of hydrogen is 3.53 $. © 2023 IEEE.

关键词： Economic analysis

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Correlation and interaction between temperature and freeze-thaw in representative regions of Antarctica

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International Journal of Digital Earth 2022年第1期15卷 2296-2318页

作者： Dong Liang Huadong Guo Qing Cheng Lu Zhang Lingyi Kong Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingPeople’s Republic of China University of Chinese Academy of Sciences BeijingPeople’s Republic of China International Research Center of Big Data for Sustainable Development Goals BeijingPeople’s Republic of China School of Computer Science China University of GeoscienceWuhanPeople’s Republic of China

As the most sensitive and direct indicator of global climate change,the freezing and thawing of the Antarctic ice sheet is of great significance for research on surface mass and energy *** this study,four representative regions in Antarctica were selected and correlation analysis,Granger causality testing,and cluster analysis were applied to comprehensively analyze the correlation and response of spatiotemporal variation in freeze-thaw and *** conclusions are as follows.(1)In the Antarctic Peninsula,a phenomenon was demonstrated that the summer shifts *** December and colder March temperatures were observed in the Amery Ice Shelf and Queen Maud Land.(2)The Antarctic Peninsula featured the most severe degree of melting among the four regions,with the largest melt area in the past 30 years appearing during the 2015/2016 ***,the number of melt days in most areas of the Antarctic Peninsula was observed to have decreased.(3)There is a strong correlation between the freeze-thaw state of the Antarctic ice sheet and temperature,as well as spatial differences among regions,but the data were clustered at different time scales.

关键词： Antarctic ice sheet Big Earth Data freeze-thaw microwave remote sensing snowmelt temperature

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Automated Heartbeat Classification for Arrhythmia Patients Using a Deep Convolutional Neural Network

Automated Heartbeat Classification for Arrhythmia Patients U...

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International Conference on Image and Signal Processing and their Applications (ISPA)

作者： Saoueb Kerdoudi Larbi Guezouli Abdessalam Hattab Tahar Dilekh Computer Science Department LaSTIC Laboratory University of Batna 2 Batna Algeria LEREESI Laboratory of Renewable Energy Energy Efficiency and Smart Systems Higher National School of Renewable Energies Environment and Sustainable Development Batna Algeria Computer Science Department LAMIE Laboratory University of Batna 2 Batna Algeria

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

The electrocardiogram (ECG) is widely used for diagnosing heart diseases, including arrhythmia, due to its noninvasive nature and simplicity. Accurate detection and classification of arrhythmic types are crucial in preventing heart disease and reducing mortality. To enhance ECG heartbeat classification, we propose an automated system based on a fine-tuned deep convolutional neural network consisting of 13 residual blocks with 28 layers in total. This model was trained using a dataset of 103247 single-lead ECG recordings. Our deep convolutional neural network achieved remarkable results by validating the independent test dataset from the MIT-BIH Arrhythmia Database. It demonstrated an Accuracy of 99%, a Macro avg Precision of 96%, a Macro avg Recall of 93%, a Weighted avg of 99%, and an impressive Macro avg F1-score of 94%. Notably, our approach has demonstrated superior performance to the original architecture, with a 3% increase in F1-score. These findings showcase the potential of our improved deep learning approach to effectively classify a wide range of arrhythmias from single-lead ECGs, yielding high diagnostic performance comparable to that of cardiologists.

关键词： Heart Heart beat Databases Arrhythmia Electrocardiography Network architecture Probability distribution

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Enhanced Parameter Extraction of Photovoltaic Models Through the Hybridization of Ant Lion Optimizer and Cuckoo Search (ALOCS) 2nd

Enhanced Parameter Extraction of Photovoltaic Models Through...

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2nd International Conference on Green Energy Conversion System, ICGECS 2023

作者： Youssef, Rehouma Mohamed, Naoui Aicha, Degla Bilal, Danoune Mohammed Assad, Hamida Mohamed Lassaad, Sbita Abdelmoumen, Gougui LAGE Laboratory University of Ouargla Ouargla30000 Algeria LEVRES Laboratory University of El Oued EL Oued39000 Algeria Research Unit of Energy Processes Environment and Electrical Systems ENIG University of Gabés Gabés6029 Tunisia Centre de Dévelopment des Energies Renouvelables—CDER 62 Route de l’observatoire Bouzareah Algeria Sustainable Development and Computer Science Laboratory SDCS-L Ahmed Draia University Adrar Algeria

ISBN: (纸本)9789819761470

The identification of photovoltaic (PV) model unknown parameters using measured characteristic curves is of great importance for designers involved in modelling, simulation, and control of PV systems. This paper introduces an enhanced heuristic algorithm, namely ALO-CS (Ant Lion Optimizer-Cuckoo Search), which combines the strengths of both ALO and CS optimization algorithms. The primary objective is to accurately extract the parameters of various commercial PV modules. To the best of our knowledge, this novel approach has not been previously explored in the literature, making it a unique contribution. In order to evaluate its effectiveness, a comparative analysis is conducted against several state-of-the-art methods. The experimental and analytical results demonstrate that the proposed Hybrid ALO-CS algorithm outperforms improved JAYA and other methods in terms of accuracy and quality, establishing its competitive advantage. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Ant lion optimizer Cuckoo search optimization Extraction Photovoltaic cell PV panel

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Automated Extraction of Active Offshore Oil/Gas Platforms Based on High-Spatial Resolution SDGSAT-1/GLI Data: A Case Study in the Northern Gulf of Mexico 2

Automated Extraction of Active Offshore Oil/Gas Platforms Ba...

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2023 2nd International Conference on Environmental Remote Sensing and Geographic Information Technology, ERSGIT 2023

作者： Chen, Zhongzhong Yan, Lin Qiu, Yujia Liang, Yueji Li, Xiao-Ming College of Geomatics and Geoinformation Guilin University of Technology Guilin541004 China International Research Center of Big Data for Sustainable Development Goals Beijing100094 China Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China School of Computer and Information Engineering Henan University Kaifeng475001 China

ISBN: (纸本)9781510672949

The acquisition of spatial distribution information on active offshore oil/gas platforms (AOOP) is of importance for effective ocean management and the comprehensive study on marine carbon emissions. In recent years, the methodological framework for AOOP extraction using low-light remote sensing imagery has emerged as a novel and promising approach. Consequently, in this study, we utilized high-resolution low-light images obtained from the Glimmer Imager (GLI) payload aboard the sustainable development Goals science Satellite 1 (SDGSAT-1) to facilitate the automatic extraction of AOOP. We applied a time-series low-light remote sensing (TLLRS) method for automatic extraction of AOOP in the northern Gulf of Mexico for the year 2022. The results indicate that the TLLRS method achieves a remarkable precision rate of 95.31% in the automatic extraction of AOOP, with an overall accuracy of 84.92%. Our findings demonstrate the feasibility and efficacy of applying SDGSAT-1 GLI data to monitor AOOP at large-scale. © 2024 SPIE.

关键词： Remote sensing

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Mapping mountain glaciers using an improved U-Net model with cSE

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International Journal of Digital Earth 2022年第1期15卷 463-477页

作者： Suzheng Tian Yusen Dong Ruyi Feng Dong Liang Lizhe Wang School of Computer Science China University of GeosciencesWuhanPeople’s Republic of China Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingPeople’s Republic of China University of Chinese Academy of Sciences Chinese Academy of SciencesBeijingPeople’s Republic of China International Research Center of Big Data for Sustainable Development Goals BeijingPeople’s Republic of China

Global warming is melting *** in mountain glaciers have a tremendous impact on human *** identification and extraction of glaciers from satellite images are ***,when studying glaciers,materials surrounding the glacier have high spectral similarity to glaciers and are easily misclassified in the identification ***,in this study of glacier extraction,we used an improved U-Net model(a channel-attention U-Net)to map *** model was trained on Landsat 8 Operational Land Imager(OLI)data and a Shuttle Radar Topography Mission(SRTM)digital elevation model(DEM),and was tested on glaciers in the Pamir *** results show that the channel-attention U-Net identifies glaciers with relatively high accuracy compared to U-Net and *** obtained results were fine-tuned by the conditional random field model,effectively reducing background misidentification.

关键词： U-Net channel-attention mechanism conditional random field glacier extraction Pamir Plateau

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Integration of Photovoltaic, Lithium Battery, and Supercapacitor Technologies for Enhanced DC Voltage in Standalone Microgrids

Integration of Photovoltaic, Lithium Battery, and Supercapac...

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Energy Transition and Security (ICETS), International Conference on

作者： Taibi Abdelhalim Laroussi Kouider Rouibah Abdelkader Mohamed Amine Hartani Applied Automation and Industrial Diagnostics Laboratory (LAADI) University Ziane Achour of Djelfa Djelfa Algeria Sustainable Development and Computer Science Laboratory SDCS-L Ahmed Draia University Algeria

In this study, photovoltaic (PV) panels, lithium battery storage systems, and supercapacitors are integrated to enhance the reliability and stability of standalone microgrids. Despite their importance, standalone microgrids face challenges relating to intermittent energy sources and voltage fluctuations in remote and off-grid *** supercapacitors in conjunction with batteries can enhance power delivery and protect battery systems. This study investigates how supercapacitors can enhance energy efficiency, extend battery life, and ensure a robust power supply. The advantages of supercapacitor-battery hybrid systems, as well as mechanisms that ensure seamless energy management and battery protection, are explored in this study. In energy storage and electrification applications, these hybrid systems provide enhanced performance, reliability, and longevity by utilizing supercapacitors. It has been found that voltage stability and energy management have been significantly improved, indicating the potential for sustainable energy solutions in remote locations.

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Atomistic Behavior of Deformed Au Thin Film during the Indentation Process 4

Atomistic Behavior of Deformed Au Thin Film during the Inden...

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4th International Conference on Innovative Research in Applied science, Engineering and Technology, IRASET 2024

作者： Ou-Khouya, Abdelkarim Mes-Adi, Hassane Taoufiki, Meryem Ibrahim, Imane Ait El Harfouf, Amin Herbazi, Rachid Tahiri, Mohamed Khouribga National School Of Applied Sciences Sultan Moulay Slimane University Process Engineering Computer Science And Mathematics Laboratory Khouribga25000 Morocco Sultan Moulay Slimane University Faculty Of Sciences And Techniques Sustainable Development Laboratory Beni-Mellal Morocco Mohamed V University Laboratory Of Condensed Matter And Interdisciplinary Sciences Cnrst Labeled Research Unit Faculty Of Sciences Departement Of Physics Rabat Morocco University Of Sultan Moulay Slimane Polydisciplinary Faculty Of Khouribga Department Of Physics Khouribga Morocco Tangier Morocco

ISBN: (纸本)9798350309508

In this study, we investigate the mechanical properties of gold (Au) materials using molecular dynamics simulations. In this simulation, the nanoindentation process was performed to analyze the deformation defects and hardness properties of Au under different indentation velocities. The results suggest that the deformation behavior of the Au specimen was affected by different indentation velocities. These findings were confirmed by examining the load-displacement curve, which indicated elastic deformation through the appearance of a linear load-displacement relationship at low indentation velocities. In contrast, plastic deformation was identified by the presence of intensified serrations in the load-displacement curve at higher indentation velocities. Under such conditions, the hardness exhibited minimal variation when the indenter velocity increased from 5 mls to 10 mls. However, a significant increase in hardness was noted when the indentation velocity was further raised to 15 mls. © 2024 IEEE.

关键词： Molecular dynamics

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Intelligent Control Based in Neural-Fuzzy of Adaptive Backstepping for The Double Stator IPMSM Powered by a Five-Level NPC Inverter

Intelligent Control Based in Neural-Fuzzy of Adaptive Backst...

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Electric And Power Engineering (EPEi), IEEE International Conference And Exposition On

作者： Rabie Benaissa Smail Mansouri Omar Ouledali Department of Electrical Engineering Laboratory for Sustainable Development and Computer Science Faculty of Sciences and Technology University of Adrar Algeria Department of Hydrocarbons and Renewable Energies Laboratory for Energy Environment and Information Systems Faculty of Sciences and Technology University of Adrar Algeria

ISBN: (数字)9798350356199

ISBN: (纸本)9798350356205

This article supplies a proposed approach Neuro Fuzzy Controller (NFC)-Adaptive Backstepping Controller (ABC)-Space Vector Modulation (SVM) for a five-level NPC inverter-Double Stator Interior Permanent Magnet Synchronous Motor (DSIPMSM). This paper’s primary objective is to enhance DSIPMSM’s performance by the use of strong control using the proposed approach. Given its benefits—including high torque density, high efficiency, high power density, and minimal maintenance—DSIPMSM, have recently been the focus of much research. Using the input-output linearization approach and Lyapunov stability theory, asymptotically stable trajectory-following dynamics are demonstrated using nonlinear adaptive backstepping control. The use of fuzzy logic and intelligence-based controllers are increasingly being used to enhance traditional control’s performance and output. In addition, the fuzzy logic controller has a lot of flaws that are presently being fixed by the extremely effective NFC tool. The proposed method’s worth was demonstrated by the simulation results in terms of durability, effective tracking dynamics, precision, and good disturbance rejection with little ripple.

关键词： Fuzzy logic Adaptation models Backstepping Torque Simulation Modulation Stators Vectors Inverters Lyapunov methods

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