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2023 International Conference on Advances in Electronics, Control and Communication systems, ICAECCS 2023

作者： Adane, Amar Haicheur, Ichrak Amani Lebza, Amani Rezzag Faculty of Electrical Engineering Usthb Laboratory Laboratory of Image Processing and Radiation Telecommunication Department Algiers Algeria

ISBN: (纸本)9781665463102

In this paper, a smart system suitable for environmental studies, is presented. This weather acquisition system is built using an Arduino uno and Raspberry Pi3. It is equipped with temperature, humidity, air quality, and solar radiation detector. The Arduino card controls the instrumentation made of the four weather sensors and the experimental data are stored using specific software developed around the Raspberry Pi3. This system can be managed via internet with a smartphone or laptop. Experimental results are obtained with this smart system. In particular, they are used to estimate the risk of fire in the region under study. © 2023 IEEE.

关键词： Risk perception

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Improvement of the 2.4 GHz SDR Radar- range using optimised Cantennas

Improvement of the 2.4 GHz SDR Radar- range using optimised ...

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2023 International Conference on Advances in Electronics, Control and Communication systems, ICAECCS 2023

作者： Adane, Amar Himene, Sofia Cherfi, Djamila Faculty of Electrical Engineering Usthb Laboratory Laboratory of Image Processing and Radiation Telecommunication Department Algiers Algeria

ISBN: (纸本)9781665463102

In this paper, a Doppler SDR Radar equipped with Adalm-Pluto SDR and Cantennas, is presented. This Radar works around 2.4 GHz. The Cantennas are made of cans acting as circular antennas. In order to improve the range of the Radar, a parametric study is implemented to optimize the matching and radiation features of these antennas. This study mainly consists in tuning the length and the width of the Cantennas so as to reduce the return loss (S11). These antennas were tested with the Doppler SDR radar. These tests allow getting the antenna which can yield accurate evaluation of the velocity of a fan propeller in a large range. Finally, two ameliorated Cantennas where built and experimented, showing that they can account for such a velocity. © 2023 IEEE.

关键词： Doppler radar

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Maintenance dynamic scheduling for a Tunisian railway transport system

Maintenance dynamic scheduling for a Tunisian railway transp...

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2024 International Conference on Control, Automation and Diagnosis, ICCAD 2024

作者： Mellouli, Sarra Mhalla, Anis Dutilleul, Simon Collart Messaoud, Hassani Laboratory of Automatic Signal and Image Processing Laratsi Monastir Tunisia Laboratory of Automation Electrical Systems Environment Laese Monastir Tunisia Estas Laboratory University Gustave Eiffel Cosys Department Lille France

ISBN: (纸本)9798350361025

The developments reported in this paper are devoted to the dynamic scheduling of rail transport systems. In this context, our study focuses on implementing an algorithm for solving railway planning with predictable or unexpected demands. The system modeling process uses P-time stochastic Petri nets. In order to improve the efficiency and punctuality of rail transport. A method for minimizing disruptions by managing maintenance is proposed. The paper's contribution is a scheduling algorithm that prioritizes maintenance tasks according to a dynamic criticality. This dynamic criterion incorporates real-time information provided by a supervisory rail system layer (a SCADA system). The STPN is used for modeling system operation. It supplies a mathematical framework for disturbance detection and prognosis. The presented work constitutes a first step towards adapting the digital twin concepts for the maintenance of weakly instrumented railway infrastructures. © 2024 IEEE.

关键词： Petri nets

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Spontaneous Recovery in Directed Dynamical Networks

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engineering 2024年第6期37卷 208-214页

作者： Xueming Liu Xian Yan H.Eugene Stanley School of Artificial Intelligence and Automation&The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems&the Key Laboratory of Image Processing Huazhong University of Science and TechnologyWuhan 430074China Center for Polymer Studies Department of PhysicsBoston UniversityBostonMA 02215USA

Complex networked systems,which range from biological systems in the natural world to infrastructure systems in the human-made world,can exhibit spontaneous recovery after a failure;for example,a brain may spontaneously return to normal after a seizure,and traffic flow can become smooth again after a *** studies on the spontaneous recovery of dynamical networks have been limited to undirected ***,most real-world networks are *** fill this gap,we build a model in which nodes may alternately fail and recover,and we develop a theoretical tool to analyze the recovery properties of directed dynamical *** find that the tool can accurately predict the final fraction of active nodes,and the prediction accuracy decreases as the fraction of bidirectional links in the network increases,which emphasizes the importance of directionality in network *** to different initial states,directed dynamical networks may show alternative stable states under the same control parameter,exhibiting hysteresis *** addition,for networks with finite sizes,the fraction of active nodes may jump back and forth between high and low states,mimicking repetitive failure-recovery *** findings could help clarify the system recovery mechanism and enable better design of networked systems with high resilience.

关键词： Network resilience Directed dynamical networks Spontaneous recovery

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Evaluation Techniques for PolSAR Speckle Filtering

Evaluation Techniques for PolSAR Speckle Filtering

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2023 International Conference on Earth Observation and Geo-Spatial Information, ICEOGI 2023

作者： Souhila, Boutarfa Youcef, Smara Chaimaa, Youcef Radia, Ballah Laboratory of Innovative Technologies Department of Electrical Engineering and Industrial Computing Bordj El Kiffan Algiers16087 Algeria Laboratory of Image Processing and Radiation Faculty of Electrical Engineering Department of Telecommunications Bab Ezzouar Algiers16111 Algeria

ISBN: (纸本)9798350396720

Speckle noise is the biggest drawback that affects polarimetric SAR (Synthetic Aperture Radar) images. Due to its multiplicative nature, it degrades their quality, complicates their interpretation and reduces the information accuracy. Its effect is reduced by applying polarimetric synthetic aperture radar (PolSAR) filtering methods. In the literature, there are several methods of PolSAR filtering, it is not obvious to choose the most effective filter, and among the techniques for evaluating the performance of these filters, it is difficult to find the best analysis method that leads to the best filtering quality without information loss. In this paper, we present a comparative study of evaluation methods for polarimetric SAR filters considering three criteria: smoothing of homogeneous areas, edge preservation and conservation of polarimetric information. In this work, we propose a more simplified approach to evaluate a polarimetric SAR filter. Each criterion includes study techniques that will help to identify the analysis method that will facilitate the selection of the best filter. © 2023 IEEE.

关键词： Speckle

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Surrogate-Assisted Multiobjective Gene Selection for Cell Classification From Large-Scale Single-Cell RNA Sequencing Data

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IEEE Transactions on Evolutionary Computation 2025年第3期29卷 601-615页

作者： Lin, Jianqing He, Cheng Jiang, Hanjing Huang, Yabing Jin, Yaochu Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Wuhan430074 China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Wuhan430074 China Renmin Hospital of Wuhan University Department of Pathology Wuhan430060 China Westlake University Trustworth and General Artificial Intelligence Laboratory School of Engineering Hangzhou310030 China

Accurate cell classification is crucial but expensive for large-scale single-cell RNA sequencing (scRNA-seq) analysis. Gene selection (GS) emerges as a pivotal technique in identifying gene subsets of scRNA-seq for classification accuracy improvement and gene scale reduction. Nevertheless, the rising scale of scRNA-seq data presents challenges to existing GS methods regarding performance and computational time. Thus, we propose a surrogate-assisted evolutionary algorithm for multiobjective GS to address these deficiencies. An innovative two-phase initialization method is proposed to select sparse solutions to provide preliminary insights into gene contributions. Then, a binary competitive swarm optimizer is proposed for effective global search, where a local search method is embedded to eliminate irrelevant genes for efficiency consideration. Additionally, a surrogate model is adopted to forecast classification accuracy efficiently and substitutes part of the computationally expensive classification process. Experiments are conducted on eight large-scale scRNA-seq datasets with more than 20 000 genes. The effectiveness of the proposed GS method for scRNA-seq cell classification compared with eight state-of-the-art methods is validated. Gene expression analysis results of selected genes further validated the significance of the genes selected by the proposed method in the classification of scRNA-seq data. © 1997-2012 IEEE.

关键词： Gene expression

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Robust DNN-Enabled Cooperative Spectrum Sensing 32

Robust DNN-Enabled Cooperative Spectrum Sensing

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32nd International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2024

作者： Serghini, Omar Serrano, Salvatore Semlali, Hayat Maali, Asmaa University of Messina Laboratory of Digital Signal Processing Department of Engineering Messina Italy Cadi Ayyad University Laboratory of Electrical Systems Energy Efficiency and Telecommunications Marrakesh Morocco Royal Naval School of Casablanca Casablanca Morocco

ISBN: (纸本)9789532901382

In this contribution, we investigate cooperative spectrum sensing in cognitive radio networks using a deep neural network approach. Our proposed architecture leverages the strengths of both a one dimentional convolutional neural network and a bidirectional long short-term memory network. This combined approach aims to effectively learn the activity patterns of primary users for accurate spectrum sensing. The signal generation process incorporates diverse modulation techniques commonly used in communication systems. Additionally, the channel model considers complexities encountered in real-world deployments. These complexities mimic the challenges of multipath propagation and relative motion, making the training data more realistic. The performance of the proposed deep neural network is compared to benchmark methods using only CNN or LSTM at the secondary user level. We evaluate the models using receiver operating characteristic curves and probability of detection for various signal-to-noise ratio levels. The simulation results showcase the effectiveness of the proposed DNN, achieving superior probability of detection compared to the benchmarks and potentially surpassing state-of-the-art methods, particularly demonstrating very good performance at very low SNR values. © 2024 University of Split, FESB.

关键词： Signal to noise ratio

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Learning Probabilistic Coordinate Fields for Robust Correspondences

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2023年第10期45卷 12004-12021页

作者： Zhao, Weiyue Lu, Hao Ye, Xinyi Cao, Zhiguo Li, Xin Huazhong University of Science and Technology The Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Wuhan430074 China West Virginia University The Lane Department of Computer Science and Electrical Engineering MorgantownWV26506-6109 United States

We introduce Probabilistic Coordinate Fields (PCFs), a novel geometric-invariant coordinate representation for image correspondence problems. In contrast to standard Cartesian coordinates, PCFs encode coordinates in correspondence-specific barycentric coordinate systems (BCS) with affine invariance. To know when and where to trust the encoded coordinates, we implement PCFs in a probabilistic network termed PCF-Net, which parameterizes the distribution of coordinate fields as Gaussian mixture models. By jointly optimizing coordinate fields and their confidence conditioned on dense flows, PCF-Net can work with various feature descriptors when quantifying the reliability of PCFs by confidence maps. An interesting observation of this work is that the learned confidence map converges to geometrically coherent and semantically consistent regions, which facilitates robust coordinate representation. By delivering the confident coordinates to keypoint/feature descriptors, we show that PCF-Net can be used as a plug-in to existing correspondence-dependent approaches. Extensive experiments on both indoor and outdoor datasets suggest that accurate geometric invariant coordinates help to achieve the state of the art in several correspondence problems, such as sparse feature matching, dense image registration, camera pose estimation, and consistency filtering. Further, the interpretable confidence map predicted by PCF-Net can also be leveraged to other novel applications from texture transfer to multi-homography classification. © 1979-2012 IEEE.

关键词： image registration

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Pansharpening Methods Based on a Redundant Contourlet Transform

Pansharpening Methods Based on a Redundant Contourlet Transf...

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2023 International Conference on Earth Observation and Geo-Spatial Information, ICEOGI 2023

作者： Ourabia, Soumeya Baaziz, Nadia Smara, Youcef University Center of Tipaza -Morsli Abdelah-Institut of Sciences Laboratory of Image Processing and Radiation -USTHB Departement of Electronics Tipaza Algeria University of Quebec in Outaouais - Uqo Research Laboratory in Multimedia Information Department of Computer Science and Engineering GatineauQC Canada University of Sciences and Technology Houari Boumediene -USTHB Laboratory of Image Processing and Radiation Faculty of Electrical Engineering Algiers Algeria

ISBN: (纸本)9798350396720

The pansharpening of high-resolution panchromatic (Pan) image and low-resolution multispectral (MS) images represents an important task in the remote sensing field. It allows the joint exploitation of the information derived from both types of images. However, this may cause a distortion of spectral information or a lack in details and structures. The multiresolution analysis using wavelet transforms has proved its efficiency in the pansharpening domain, due to the representation of the image content over different resolution levels. In image fusion applications, we always need more detail information to be incorporated in the pansharpening procedure in order to produce enhanced results. However, the limitation of the wavelet transform to three types of oriented detail coefficients prevents this need from being met. To overcome this limitation, we propose to use the redundant contourlet transform (RCT) which extracts a richer multiscale directional information from the image. For this purpose, two RCT-based pansharpening methods are introduced and suitable data fusion procedures are described. We conducted several experiments on two different datasets acquired respectively by ALSAT-2A and IKONOS satellites. The visual results as well as quantitative results from evaluation metrics demonstrate the performance of the proposed methods. © 2023 IEEE.

关键词： image enhancement

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Multi-objective Optimal Operation of Centralized Battery Swap Charging System with Photovoltaic

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Journal of Modern Power systems and Clean Energy 2022年第1期10卷 149-162页

作者： Yuanzheng Li Yihan Cai Tianyang Zhao Yun Liu Jian Wang Lei Wu Yong Zhao School of Artificial Intelligence and Automation Ministry of Education Key Laboratory of Image Processing and Intelligence ControlHuazhong University of Science and TechnologyWuhanChina School of Electrical and Electronic Engineering Nanyang Technological UniversitySingaporeSingapore College of Mechatronics and Control Engineering Shenzhen UniversityShenzhenChina Department of Electrical&Computer Engineering Stevens Institute of TechnologyHobokenUSA

Electric vehicles(EVs)are widely deployed throughout the world,and photovoltaic(PV)charging stations have emerged for satisfying the charging demands of EV *** paper proposes a multi-objective optimal operation method for the centralized battery swap charging system(CBSCS),in order to enhance the economic efficiency while reducing its adverse effects on power *** proposed method involves a multi-objective optimization scheduling model,which minimizes the total operation cost and smoothes load fluctuations,***,we modify a recently proposed multi-objective optimization algorithm of non-sorting genetic algorithm III(NSGA-III)for solving this scheduling ***,simulation studies verify the effectiveness of the proposed multi-objective operation method.

关键词： Multi-objective optimization electric vehicle battery swap charging system scheduling photovoltaic

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