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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Ines Ben Rouighi Hajer Chtioui Imen Jegham Anouar Ben Khalifa Ecole Nationale d’Ingénieurs de Sousse LATIS-Laboratory of Advanced Technology and Intelligent Systems Université de Sousse Sousse Tunisie Institut National des Technologies et des Sciences du Kef Université de Jendouba Le Kef Tunisie

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

Deploying drones with deep-learning capabilities for real-time object detection is a trendsetting strategy, particularly in dynamic environments such as intelligent Transportation systems. Drones, or Unmanned Aerial Vehicles, offer advantages including a wide field of view, cost-effectiveness, and operational efficiency, making them ideal for perception and surveillance in dynamic settings. However, drones face several challenges in terms of on-board computational capabilities, constraining the deployment of complex algorithms for aerial imagery analysis. In this paper, we exhaustively study the challenges of real-time object detection for drones, emphasizing the adaptability and effectiveness of deep learning-based detectors. We fine-tune and evaluate the six most used scaled versions of real-time object detectors for drone-imagery, using a benchmark, tailored for drone-captured data, to assess detection accuracy, inference speed, and computational efficiency. Our study proves that YOLOv5n excels in terms of inference speed at 454 FPS, but with lower precision, while YOLOv8n surpasses in precision but requires more resources and longer inference times. Larger versions show moderate accuracy improvement but demand increased computational resources and extended inference duration.

关键词： YOLO Accuracy Computational modeling Heuristic algorithms Detectors Real-time systems Computational efficiency Vehicle dynamics Faces Drones

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Generalization of Reflection Modeling in Complex Cable Structure with Impedance Mismatches 17

Generalization of Reflection Modeling in Complex Cable Struc...

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17th International Workshop on Impedance Spectroscopy, IWIS 2024

作者： Haddad, Dhia Ben Amara, Najoua Essoukri Kanoun, Olfa Technische Universität Chemnitz Professorship Measurement and Sensor Technology Chemnitz Germany Université de Sousse Ecole Nationale d'Ingénieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia

ISBN: (纸本)9798331507626

Cable networks are essential in modern systems, but they can develop defects due to environmental factors or wear, leading to signal degradation or reduced performance. These defects cause signal reflections in transmission lines due to impedance mismatches, either within the cables or between the cables and their port loads. Such reflections can result from junctions, soft faults (partial impedance changes), or hard faults, i.e., open or short circuits. Diagnosing these faults, especially using Time-Domain Reflectometry (TDR), requires accurately modeling how impedance mismatches affect signal reflections. This paper presents a model that takes a comprehensive approach to addressing various sources of impedance mismatches. It covers junctions, soft and hard faults, and mismatches between cables and connected devices. The model's thoroughness is evident in its ability to handle complex scenarios such as heterogeneous junctions, soft faults, multi-path reflections, input port reflections, and multi-load reflections. Additionally, it evaluates signal reflection measurability based on the components of the propagation path, further enhancing its robustness. The model's accuracy is validated through simulations using the distributed RLCG cable model, comparing predicted reflection values with simulated signals. The results show strong agreement, confirming the model's effectiveness in diagnosing faults in complex cable networks. This should instill confidence in the model's practical application, as it accurately correlates signal reflections with specific defects, paving the way for efficient fault diagnosis. © 2024 IEEE.

关键词： Reflectometers

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Enhancing rheology and mechanical properties of DLP 3D-printed Si_(3)N_(4) materials via composition optimization and gas-pressure sintering

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International Journal of Minerals,Metallurgy and Materials 2025年第5期32卷 1220-1233页

作者： Qing Qin Gang Xiong Lin Han Yujuan Zhang Zhen Shen Changchun Ge Institute of Powder Metallurgy and Advanced Ceramics School of Materials Science and EngineeringUniversity of Science and Technology BeijingBeijing 100083China State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and TechnologyInstitute of AutomationChinese Academy of SciencesBeijing 100190China

Digital light processing(DLP)is a crucial additive manufacturing(AM)technique for producing high-precision ceramic *** study aims to optimize the formulation of Si_(3)N_(4)slurry to enhance both its performance and manufacturability in the DLP process,and investigate key factors such as particle size distribution,photopolymer resin monomer ratios,and dispersant types to im-prove the slurry’s rheological *** these optimizations,a photosensitive Si_(3)N_(4)slurry with 50vol%solid content was de-veloped,exhibiting excellent stability,and low viscosity(2.48 Pa·s at a shear rate of 12.8 s^(-1)).The effects of gas-pressure sintering on the material’s phase composition,microstructure,and mechanical properties were further explored,revealing that this technique significantly increases the flexural strength of the green sample from(109±10.24)to(618±42.15)*** sintered ceramics exhibited high hard-ness((16.59±0.05)GPa)and improved fracture toughness((4.45±0.03)MPa·m^(1/2)).Crack trajectory analysis revealed that crack deflec-tion,crack bridging,and the pull-out of rod-likeβ-Si_(3)N_(4)grains,are the main toughening mechanisms,which could effectively mitigate crack *** these mechanisms,crack deflection and bridging were particularly influential,significantly enhancing the frac-ture toughness of the Si_(3)N_(4)***,this research highlights how monomer formulation and gas-pressure sintering strengthen the performance of Si_(3)N_(4)slurry in the DLP three-dimensional printing *** work is expected to provide new insights for fabricat-ing complex Si_(3)N_(4)ceramic components with superior mechanical properties.

关键词： additive manufacturing Si_(3)N_(4)slurry low viscosity pressure sintering

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Attention-Modulated Feature Fusion Neural Network for Inverse Modeling of Microwave Filters

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IEEE Microwave and Wireless technology Letters 2025年第4期35卷 376-379页

作者： Guo, Linwei Cao, Weihua Hu, Wenkai Lu, Zhengyang Wu, Min China University of Geosciences School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

Inverse modeling is extensively applied in the design and tuning of microwave filters (MFs). Inverse models (IMs) take the features extracted from the high-dimensional electromagnetic parameters as input. How to make full use of features from multiple perspective is a critical issue for improving model accuracy. To solve it, this letter proposes an attention-modulated feature fusion neural network (AMFFNN). AMFFNN achieves multiperspective feature fusion (MPFF) at the input side and independent feature fusion (IFF) at the output side. In addition, feature fusion in AMFFNN is enhanced by attention modules to dynamically identify the importance of each feature. Statistical and comparative results of simulations demonstrate that AMFFNN outperforms existing methods in terms of accuracy, stability, and generalization. © 2023 IEEE.

关键词： Inverse problems

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Recent advances in photopolymerization 3D printing of alumina-ceramic

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Progress in Natural Science:Materials International 2025年第1期35卷 1-30页

作者： M.Irfan Hussain Min Xia XiaoNa Ren Zhen Shen Muhammad Jamil Changchun Ge Institute of Powder Metallurgy and Advanced Ceramics School of Material Science and Engineering University of Science and Technology Beijing State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of Sciences College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics

Digital light processing(DLP) 3D printing has a huge potential for manufacturing intricate and customized ceramic parts with high precision and cost-effectiveness. Research in this field contributes to material innovation,opening the avenues for new process designs in both scientific and industrial sectors. However, the implementation of DLP 3D printing technology in ceramic research has not yet reached the maturity level as that in polymer and tissue engineering. Necessarily, a holistic in-depth literature reporting the successful integration of alumina ceramics within DLP 3D printing technology is urgently needed. This review, systematic examines recent progress in DLP technology, focusing on photopolymer resins that incorporate UV-sensitive monomers, photoinitiators, and dispersants, as well as their synergistic effects on achieving high-quality printing, desirable material properties, and enhanced performance. Further, the review discusses key factors including post-processing characteristics such as debinding and sintering, which influence microstructure, and defect formation including microcracks, porosity and voids. Finally, the challenges associated with printing and sintering are highlighted,aiming to identify focused focused development pathways and potential solution to optimize outcomes. This analysis clarifies existing challenges and also propsoes future applications for DLP technology in the aluminaceramic field.

关键词： Al2O3 ceramics Applications Digital light processing (DLP) Post-processing Resin

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Modeling and Simulation of a Two-Phase Interleaved Boost Converter for Photovoltaic Applications

Modeling and Simulation of a Two-Phase Interleaved Boost Con...

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2023 IEEE International Conference on Artificial Intelligence and Green Energy, ICAIGE 2023

作者： Gaaloul, Yasmine Kechiche, Olfa Bel Hadj Brahim Hamouda, Mahmoud University of Sousse National Engineering School of Sousse LATIS-Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia University of Sousse ESSTHSousse HSousse4011 Tunisia HSousse4011 Tunisia

ISBN: (纸本)9798350325539

As the world clamors for renewable energy sources, DC/DC converters are increasingly indispensable tools for transforming DC voltage into the required output voltage with minimal energy loss. This research paper showcases the design and simulation of a two-phase Interleaved Boost Converter for unconventional energy sources that utilize Matlab/Simulink software. With its capacity to raise output voltage to 380V. Furthermore, the paper provides the behavior of interleaved boost converters under variable duty cycles with maximum power point tracker control. The results show the efficiency of the proposed converter for both low and high-power applications such as PV systems. © 2023 IEEE.

关键词： Maximum power point trackers

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One Sided GaN-Based Buck Converter Layout Optimization by Minimizing Power Loop Parasitics and Considering Heat Dissipation Efficiency

One Sided GaN-Based Buck Converter Layout Optimization by Mi...

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2023 IEEE International Conference on Artificial Intelligence and Green Energy, ICAIGE 2023

作者： Belguith, Mohamed Eloued, Sonia Kadi, Moncef Ben Hadj Slama, Jaleleddine Université de Sousse Ecole Nationale d'Ingénieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse Tunisia Unirouen Esigelec Irseem Rouen76000 France

ISBN: (纸本)9798350325539

GaN is an excellent selection for implementation in the transportation industry due to its high switching frequency, high power density, and high breakdown voltage. The aim of this paper is to develop a one-sided DC/DC 48V/12V GaN-based Buck converter that is simple to design and manufacturing for laboratory experiments and testing, revealing its advantages over double-sided converters. Three different layouts are suggested and compared in this investigation in order to optimize the power loop layout by minimizing its parasitic elements;those latter are extracted using Ansys software 'Q3D tool' and then included in an electrical model in the waveform viewer software 'LTspice' to evaluate their impacts on the switching node signal 'Vsw' of the half bridge configuration. An examination of current density and pathing in each layout is also presented in this study. Simple calculations are performed for thermal management, which end up resulting in the selection of a heatsink as a cooling solution. At 1 MHz cut-off frequency, the layout chosen have a power loop inductance of 0.73nH, which results in decreased ringing phenomena. © 2023 IEEE.

关键词： Finite element method

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A Transformer-based Siamese Network For Word Image Retrieval In Historical Documents 9

A Transformer-based Siamese Network For Word Image Retrieval...

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9th IEEE Smart World Congress, SWC 2023

作者： Fathallah, Abir El-Yacoubi, Mounim A. Essoukri Ben Amara, Najoua Université de Sousse Institut Supérieur de l'Informatique et des Techniques de Communication LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse4011 Tunisia Samovar Telecom SudParis Institut Polytechnique de Paris Palaiseau91120 France Université de Sousse Ecole Nationale d'Ingénieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia

ISBN: (纸本)9798350319804

The increasing availability of digitized historical documents has sparked a need for effective information processing tools to extract the valuable information contained within them. Word spotting, an area of focus in historical document analysis, involves identifying specific words within images of documents. In this paper, we propose a novel approach for word spotting in historical Arabic documents, utilizing improved feature representations for learning word images. More precisely, we put forward an end-to-end approach for generating word image descriptors, based on the Siamese vision transformer architectures. The model learning is guided by a contrastive loss objective. Additionally, we carry out transfer learning techniques by leveraging knowledge acquired from two distinct source domains to generalize model learning. The proposed approach utilizes the embedding space to evolve the word spotting system by projecting the query word image and all reference word images into the embedding space, where their similarity is determined based on their corresponding embedding vectors. Our method is evaluated on the historical Arabic VML-HD dataset and the results indicate that our approach significantly outperforms state-of-the-art methods. © 2023 IEEE.

关键词： Historical Arabic documents Learning representation Siamese network Transfer learning Vision transformer Word spotting

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CBHIR-based approach for histological image analysis on large scale datasets

CBHIR-based approach for histological image analysis on larg...

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International Conference on Cyberworlds

作者： Roua Jaafar Hedi Yazid Najoua Essoukri Ben Amara LATiS-Laboratory of Advanced Technology and Intelligent Systems ENISo Sousse Souse Tunisia LATiS-Laboratory of Advanced Technology and Intelligent Systems ENISo Sousse LISITE Laboratory ISEP Paris Paris France LATiS-Laboratory of Advanced Technology and Intelligent Systems Universite de Sousse Ecole Nationale d’ingenieurs de Sousse Souse Tunisia

Automatic analysis of histopathological images is a very challenging topic and it involves various tasks. While interpreting Whole Slide Images (WSI), pathologists require advanced tools to perform their analysis. Thus, we propose a content-based histopathological image retrieval (CBHIR) based on incremental phenotyping approach. The CBHIR aims to assist practitioners in the decision making into a diagnosis process while providing similar cases which clinicians can refer to interpret a current one. The phenotyping approach consists mainly in delving into the large histological image in order to discover the correlations that exist between the different regions. The phenotyping graph will be applied in the CBHIR system.

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Digital Image Forgery Detection with Focus on a Copy-Move Forgery Detection: A Survey

Digital Image Forgery Detection with Focus on a Copy-Move Fo...

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International Conference on Cyberworlds

作者： Sami Gazzah Lamia Rzouga Haddada Isam Shallal Najoua Essoukri Ben Amara LATIS-Laboratory of Advanced Technology and Intelligent Systems University of Sousse Sousse Tunisia

The importance of ensuring the authenticity and reliability of digital images has grown significantly, primarily due to the ease of modifying such images with the progress of digital image editing tools. Consequently, there is a growing emphasis on the development of techniques for detecting image manipulation. One particular area of focus in digital image authentication is copy-move forgery detection. This paper presents a survey and a comparative study on copy-move forgery detection techniques in digital images, databases, and evaluation metrics. The study aims to provide insights into the effectiveness of different methods in detecting copy-move forgeries. The paper discusses prominent detection techniques, including block-based, keypoint-based, transform domain, hybrid methods, deep learning, and GAN approaches. The findings highlight the strengths, weaknesses, and key similarities and differences among the approaches. This study contributes to the understanding of the state-of-the-art in copy-move forgery detection and provides guidance for future research in this field.

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