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32nd ACM International Conference on Multimedia, MM 2024

作者： Lin, Junyu Zheng, Yan Chen, Xinyue Ren, Yazhou Pu, Xiaorong He, Jing Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Medicine Biomedical Sciences The University of Queensland BrisbaneQLD Australia

ISBN: (纸本)9798400706868

Multi-view based molecular properties prediction learning has received widely attention in recent years in terms of its potential for the downstream tasks in the field of drug discovery. However, the consistency of different molecular view representations and the full utilization of complementary information among them in existing multi-view molecular property prediction methods remain to be further explored. Furthermore, most current methods focus on generating global level representations at the graph level with information from different molecular views (e.g., 2D and 3D views) assuming that the information can be corresponded to each other. In fact it is not unusual that for example the conformation change or computational errors may lead to discrepancies between views. To addressing these issues, we propose a new Cross-View contrastive unification guides Generative Molcular pre-trained model, call MolCVG. We first focus on common and private information extraction from 2D graph views and 3D geometric views of molecules, Minimizing the impact of noise in private information on subsequent strategies. To exploit both types of information in a more refined way, we propose a cross-view contrastive unification strategy to learn cross-view global information and guide the reconstruction of masked nodes, thus effectively optimizing global features and local descriptions. Extensive experiments on real-world molecular data sets demonstrate the effectiveness of our approach for molecular property prediction task. © 2024 ACM.

关键词： Contrastive Learning

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Cancelable Speaker Identification System Based on Optical-Like Encryption Algorithms

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computer Systems Science & engineering 2022年第10期43卷 87-102页

作者： Safaa El-Gazar Walid El-Shafai Ghada El-Banby Hesham F.A.Hamed Gerges M.Salama Mohammed Abd-Elnaby Fathi E.Abd El-Samie Department of Electrical Engineering Faculty of EngineeringEgyptian-Russian UniversityCairoEgypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Biometric authentication is a rapidly growing trend that is gaining increasing attention in the last *** achieves safe access to systems using biometrics instead of the traditional *** utilization of a biometric in its original format makes it usable only ***,a cancelable biometric template should be used,so that it can be replaced when it is *** biometrics aims to enhance the security and privacy of biometric *** encryption is an efficient technique to be used in order to generate cancelable biometric *** this paper,a highly-secure encryption algorithm is proposed to ensure secure biometric data in verification *** considered biometric in this paper is the speech *** speech signal is transformed into its ***,the spectrogram is encrypted using two cascaded optical encryption *** first algorithm is the Optical Scanning Holography(OSH)for its efficiency as an encryption *** OSH encrypted spectrogram is encrypted using Double Random Phase Encoding(DRPE)by implementing two Random Phase Masks(RPMs).After the two cascaded optical encryption algorithms,the cancelable template is *** verification is implemented through correlation estimation between enrolled and test templates in their encrypted *** the correlation value is larger than a threshold value,the user is *** threshold value can be determined from the genuine and imposter correlation distribution curves as the midpoint between the two *** implementation of optical encryption is adopted using its software rather than the optical *** efficiency of the proposed cancelable biometric algorithm is illustrated by the simulation *** can improve the biometric data security without deteriorating the recognition *** results give close-to-zero This values for the Equal Error Rate(EER)and close-to-one values for the Area under Receiver Operator Charact

关键词： Cancelable biometrics spectrogram OSH DRPE EER AROC

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Advanced Power and Voltage Regulation in a DC Microgrid with Solar Energy and Battery Storage 15

Advanced Power and Voltage Regulation in a DC Microgrid with...

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15th International Renewable Energy Congress, IREC 2025

作者： Elrashid, M. Rajab, Z. Elhashane, M. Younis, A. Gomez-Romero, J. Tnatin, Salah I.S Mohamed, F. Benghazi University Faculty if Engineering Electrical and Electronic Department Libya University of Granada Department of Computer Science and Artificial Intelligence Spain Omar Al-Mukhtar University Faculty of Engineering Electrical Department Libya Authority of Natural Science Research and Technology Tripoli Libya

ISBN: (纸本)9798331516772

This research investigates the modeling, design, and simulation of a microgrid with advanced energy management controller, developed using MATLAB/Simulink. This paper presents a comprehensive analysis, modeling, and simulation of a smart controller for a boost converter, using an artificial neural network (ANN) for maximum power point tracking (MPPT) to enhance power output. The study begins with a comparison between traditional MPPT techniques and the ANN-based approach. These MPPT strategies are compared in terms of their response to dynamic weather conditions (such as temperature and irradiance variations) and their ability to minimize oscillations around the maximum power point. The simulation results demonstrate that the ANN-based MPPT method outperforms the conventional P&O and IC methods, providing faster response times and higher output power. Additionally, the system's performance was evaluated under conditions of power shortage and during battery charging and discharging cycles, showing the effectiveness of the smart controller in maintaining system stability and optimizing energy management. © 2025 IEEE.

关键词： MATLAB

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Face Recognition Based on Fusion Feature Extraction Algorithms 6

Face Recognition Based on Fusion Feature Extraction Algorith...

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6th IEEE International Conference on Emerging Smart Computing and Informatics, ESCI 2024

作者： Albakri, Ibrahim Mahmood Rashid Ahmad, Muhammad Imran Md Isa, Mohd Nazrin Al-Dabagh, Mustafa Zuhaer Nayef Universiti Malaysia Perlis Faculty of Electronic Engineering Technology Perlis Malaysia Collage of Agriculture Telafer University Telafer Iraq Knowledge University Department of Computer Science Erbil Iraq

ISBN: (纸本)9798350306613

Biometric-based methods have emerged as a highly promising avenue for individual recognition, with face recognition standing out as a key application in image analysis. Facial recognition systems are affected by various image condition factors, including expressions, occlusion, poses, and illuminations. It is crucial to consider reasonable variations in illumination between gallery and probe images when developing face recognition algorithms. In the context of face verification, illumination variation significantly influences the likelihood of misclassification. Existing research lacks a focus on imaging conditions, especially regarding illumination, in face recognition systems. This research aims to identify and design a scheme to address illumination variation in facial recognition. The proposed scheme will undergo analysis and evaluation to assess its accuracy and effectiveness. The image processing in this research is divided into two phases. The first is the preprocessing phase, encompassing auto contrast balancing and noise reduction. The second phase is face processing, which involves illumination normalization, face detection, feature extraction, and face recognition. Two datasets are utilized: The first being the ORL dataset, which includes images with illumination variations, and the second being the Yale database, where images contain various noises. © 2024 IEEE.

关键词： FACE RECOGNITION Feature Extraction Fusion HOG LBP

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SA-ResNet:An Intrusion Detection Method Based on Spatial Attention Mechanism and Residual Neural Network Fusion

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computers, Materials & Continua 2025年第5期83卷 3335-3350页

作者： Zengyu Cai Yuming Dai Jianwei Zhang Yuan Feng School of Computer Science and Technology Zhengzhou University of Light IndustryZhengzhou450066China College of Software Engineering Zhengzhou University of Light IndustryZhengzhou450066China Faculty of Information Engineering Xuchang Vocational Technical CollegeXuchang461000China School of Electronic Information Zhengzhou University of Light IndustryZhengzhou450066China

The rapid development and widespread adoption of Internet technology have significantly increased Internet traffic,highlighting the growing importance of network *** Detection Systems(IDS)are essential for safeguarding network *** address the low accuracy of existing intrusion detection models in identifying network attacks,this paper proposes an intrusion detection method based on the fusion of Spatial Attention mechanism and Residual Neural Network(SA-ResNet).Utilizing residual connections can effectively capture local features in the data;by introducing a spatial attention mechanism,the global dependency relationships of intrusion features can be extracted,enhancing the intrusion recognition model’s focus on the global features of intrusions,and effectively improving the accuracy of intrusion *** proposed model in this paper was experimentally verified on theNSL-KDD *** experimental results showthat the intrusion recognition accuracy of the intrusion detection method based on SA-ResNet has reached 99.86%,and its overall accuracy is 0.41% higher than that of traditional Convolutional Neural Network(CNN)models.

关键词： Intrusion detection deep learning residual neural network spatial attention mechanism

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Improved Quaternion Discriminant Analysis for Feature Extraction and Classification of Hyperspectral Image

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 12925-12945页

作者： Wang, Xinpeng Ling, Bingo Wing-Kuen Yu, Long Dai, Qingyun Liu, Shaopeng Zhao, Jiandong Kuang, Weichao Guangdong Polytechnic Normal University Faculty of Computer Science Guangzhou China Guangdong University of Technology School of Information Engineering Guangzhou China Sun Yat-sen University School of Geography and Planning Guangzhou510275 China Dongguan University of Technology Department of Electronic Engineering and Intellectualization Dongguan China

Real domain discriminant analysis (RDA) can not solve the crosstalk of strong correlation between adjacent spectral bands, and also causes spectral information loss of hyperspectral image (HSI). As a result, the effect of feature extraction is not ideal. Besides, in the case of small samples, using quaternion discriminant analysis (QDA) based on Cos-sin Decomposition, the matrix obtained by the first orthogonal trigonometric decomposition is not a diagonal matrix, that makes the projection axis not optimal. To solve these problems, firstly, a quaternion discriminant analysis method based on stable quaternion Cossin Decomposition (QDASG) is proposed to solve the small sample problem. Secondly, this paper theoretically analyzes that when the number of projection axes in QDASG is smaller than that in traditional DA methods, the discriminant formula can achieve optimal results, and verifies this conclusion through experiments. Then, according to the number of training samples, the implementation process of QDA is discussed in two cases. Finally, spatial filtering is used to extract spatial information, and the distance quotient formula between classes is proposed as the standard for selecting the the optimal number of stacking layers for the filter. Experimental results show that this method is effective compared with deep learning method and and other traditional machine learning methods, especially in the case of small samples. © 2008-2012 IEEE.

关键词： Discriminant analysis

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Leveraging Hybrid LSTM-Attention-CatBoost Model for Complex Energy Behavior Forecasting 3

Leveraging Hybrid LSTM-Attention-CatBoost Model for Complex ...

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3rd International Conference on Smart Grids and Energy Systems, SGES 2024

作者： Lu, Lu Shen, Zhengdong Li, Shuting Wang, Weili Faculty of Science and Technology Beijing Normal University·Hong Kong Baptist University United International College Zhuhai China Department of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing China School of Computer Science and Engineering Faculty of Innovation Engineering Macau University of Science and Technology China School of Computer Science South China Normal University Guangzhou China

ISBN: (纸本)9798331539634

We present an advanced energy prediction model that addresses energy imbalance by integrating Long Short-Term Memory (LSTM) with Attention Mechanism for time-series analysis and categorical boosting (CatBoost) for categorical feature optimization. This model accurately predicts the complex energy behaviors of prosumers who both generate and consume energy. Simulation results show that our model outperforms traditional methods with the lowest Mean Absolute Error (MAE) of 48.514. By achieving such a high level of accuracy, this model improves grid operation efficiency, offers a practical solution for smart grid management. © 2024 IEEE.

关键词： Attention Mechanism CatBoost Data Processing Energy Forecasting LSTM

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Bilateral Coupled Epsilon Negative Metamaterial for Dual Band Wireless Communications

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computers, Materials & Continua 2022年第4期71卷 1263-1281页

作者： Md Mhedi Hasan Mohammad Tariqul Islam Md Moniruzzaman Mohd Hafiz Uddin Norsuzlin Binti Mohd Sahar Md Samsuzzaman Department of Electrical Electronic and Systems Engineering Faculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaSelangor43600Malaysia Space Science Centre Institute of Climate ChangeUniversiti Kebangsaan MalaysiaSelangor43600Malaysia Department of Computer and Communication Engineering Faculty of Computer Science and EngineeringPatuakhali Science and Technology UniversityPatuakhali8602Bangladesh

This work presents a dual band epsilon negative(ENG)metamaterial with a bilateral coupled split ring resonator(SRR)for use in C and X band wireless communication *** traditional split-ring resonator(SRR)has been amended with this engineered *** proposed metamaterial unit cell is realized on the 1.6 mm thick FR-4 printed media with a dimension of 10×10 *** resonating patch built with a square split outer *** interlinked inner rings are coupled vertically to the outer ring to extend its electrical length as well as to tune the resonance *** simulation is performed using CST studio suite 2019 to design and performance *** transmission coefficient(S21)of the proposed unit cell and array configuration exhibits two resonances at 6.7 and 10.5 GHz with wide bandwidth extended from 4.86 to 8.06 GHz and 10.1 to 11.2 GHz,*** permittivity is noted at frequencies between 6.76–9.5 GHz and 10.5–12 GHz,consecutively,with near-zero refractive index and *** optimal EMR value depicts the compactness of the proposed *** 1×2,2×2 and 4×4 arrays are analyzed that shows similar response compared to the unit *** results of the 2×2 array shows the close similarity of S21 response as compared to *** observed properties of the proposed unit cell ascertain its suitability for wireless communications by enhancing the gain and directivity of the antenna system.

关键词： Metamaterial epsilon negative near-zero index split ring resonator wireless communications

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Gauss Gradient and SURF Features for Landmine Detection from GPR Images

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computers, Materials & Continua 2022年第6期71卷 4457-4486页

作者： Fatma M.El-Ghamry Walid El-Shafai Mahmouad I.Abdalla Ghada M.El-Banby Abeer D.Algarni Moawad I.Dessouky Adel S.Elfishawy Fathi E.Abd El-Samie Naglaa F.Soliman Department of Electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazigSharqia44519Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Recently,ground-penetrating radar(GPR)has been extended as a well-known area to investigate the subsurface ***,its output has a low resolution,and it needs more processing for more *** paper presents two algorithms for landmine detection from GPR *** first algorithm depends on a multi-scale technique.A Gaussian kernel with a particular scale is convolved with the image,and after that,two gradients are estimated;horizontal and vertical ***,histogram and cumulative histogram are estimated for the overall gradient *** bin values on the cumulative histogram are used for discrimination between images with and without ***,a neural classifier is used to classify images with cumulative histograms as feature *** second algorithm is based on scale-space analysis with the number of speeded-up robust feature(SURF)points as the key parameter for *** addition,this paper presents a framework for size reduction of GPR images based on decimation for efficient *** further classification steps can be performed on images after *** sensitivity of classification accuracy to the interpolation process is studied in detail.

关键词： GPR images cumulative histogram gradient image neural classifier SURF

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Secure Audio Transmission Over Wireless Uncorrelated Rayleigh Fading Channel

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computers, Materials & Continua 2022年第1期70卷 1603-1615页

作者： Osama S.Faragallah M.Farouk Hala S.El-sayed Mohsen A.M.El-bendary Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science and Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electrical Engineering Faculty of EngineeringMenoufia UniversityShebin El-Kom32511Egypt Department of Electronics Technology Faculty of Technology and EducationHelwan UniversityCairoEgypt

Audio communications and computer networking play essential roles in our daily lives,including many domains with different *** in these technologies are *** consequence,there is a dire need to secure these technologies up to *** paper presents an efficient model for secure audio signal transmission over the wireless noisy uncorrelated Rayleigh fading ***,the performance of the utilized multiple secret keys-based audio cryptosystem is analyzed in different transformation *** discrete cosine transform(DCT),the discrete sine transform(DST),and the discrete wavelet transform(DWT)are investigated in the utilizedmultiple secret key-based audio *** results show consistent results with the wireless noisy *** performance of the proposed multiple secret keys-based audio cryptosystem can be ranked concerning the employed domain as DWT,DCT,and DST transform *** simulation experiments proved that the presented multiple secret keysbased audio cryptosystemfor audio signals transmitted over the wireless noisy uncorrelatedRayleigh fading channel achieves reliable and secure wireless link utilizing combined multi security layers.

关键词： Audio communications encryption uncorrelated Rayleigh fading channel

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