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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： Ismail, Eman Ali, Abdelhay Aly, Omar A. M. Abo-Zahhad, Mohammed Assuit University Faculty of Engineering Department of Electrical Engineering Assuit Egypt Egypt-Japan University of Science and Technology Faculty of Electronics Communications and Computer Engineering Department of Electronics and Communications Engineering Alexandra Egypt

ISBN: (纸本)9798350323511

Recent advancements in deep learning have led to the emergence of autoencoder-based (AE) wireless communication systems, presenting a promising approach to tackle the challenges posed by conventional mathematical models. In this research, a thorough evaluation and analysis of the performance of deep learning AE-based wireless communication systems is conducted. Specifically, our investigation focuses on employing the additive white Gaussian noise (AWGN) channel and explores the impact of varying signal-to-noise ratio (SNR) conditions during the AE training process on system performance. The results show that training the autoencoder under diverse SNR conditions, particularly with an extended number of epochs, surpasses the performance of a fixed-trained autoencoder regarding block error rate (BLER). Additionally, a comparison of BLER between multiple AE models and traditional mathematical representations used in communication systems is conducted. The obtained findings indicate that deep learning AE-based wireless communication systems exhibit promising performance compared to conventional models, underscoring their potential as an effective solution for wireless communication systems. © 2023 IEEE.

关键词： Signal to noise ratio

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Dynamic control and manipulation of near-fields using direct feedback

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Light(Science & Applications) 2024年第12期13卷 3151-3157页

作者： Jacob Kher-Aldeen Kobi Cohen Stav Lotan Kobi Frischwasser Bergin Gjonaj Shai Tsesses Guy Bartal The Andrew&Erna Viterbi Faculty of Electrical&Computer Engineering Technion—Israel Institute of TechnologyHaifa 3200003Israel Department of Physical Engineering Polytechnic University of Tirana—Faculty of Physical&Math EngineeringTirana 1000Albania Faculty of Medical Sciences Albanian UniversityDurrës StreetTirana 1000Albania Department of Physics MIT—Harvard Center for Ultracold Atoms and Research Laboratory of ElectronicsMassachusetts Institute of TechnologyCambridgeMAUSA

Shaping and controlling electromagnetic fields at the nanoscale is vital for advancing efficient and compact devices used in optical communications,sensing and metrology,as well as for the exploration of fundamental properties of light-matter interaction and optical ***-time feedback for active control over light can provide a significant advantage in these endeavors,compensating for ever-changing experimental conditions and inherent or accumulated device *** nearfield microscopy,being slow in essence,cannot provide such a real-time feedback that was thus far possible only by scattering-based ***,we present active control over nanophotonic near-fields with direct feedback facilitated by real-time near-field *** use far-field wavefront shaping to control nanophotonic patterns in surface waves,demonstrating translation and splitting of near-field focal spots at nanometer-scale precision,active toggling of different near-field angular momenta and correction of patterns damaged by structural defects using feedback enabled by the real-time *** ability to simultaneously shape and observe nanophotonic fields can significantly impact various applications such as nanoscale optical manipulation,optical addressing of integrated quantum emitters and near-field adaptive optics.

关键词： scattering metrology feedback

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Statistical-based HRV Feature Importance Evaluation for Arrhythmia and Atrial Fibrillation Classification 12

Statistical-based HRV Feature Importance Evaluation for Arrh...

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12th Mediterranean Conference on Embedded Computing, MECO 2023

作者： Tihak, Amina Boskovic, Dusanka University of Sarajevo Faculty of Electrical Engineering Department of Automatic Control and Electronics Sarajevo Bosnia and Herzegovina

ISBN: (纸本)9798350322910

The paper evaluates statistical significance of the differences in the feature values necessary to differentiate the signals corresponding to cardiac arrhythmia (AR) and atrial fibrillation (AF). The initial set of heart rate variability (HRV) features includes time and frequency domain metrics, as well as geometric metrics based on the Poincare diagram. Due to non-uniformity of the heart rate signal, frequency domain features are calculated using two approaches: the Lomb-Scargle method for spectral analysis for non-uniform signals, and Welch method for uniform signals, but after the signal interpolation and resampling. Selection of an appropriate statistical test was depending on the distribution of feature values. Normal distribution allowed use of parametric ANOVA test and otherwise non-parametric Wilcoxon-Mann-Whitney test were used. The statistical tests indicated statistically significant difference between the two observed groups of signals of interest with respect to the evaluated feature. The success of the classification depends on the well-chosen features according to their importance. In the paper, statistical tests resulted in selection of 27 features out of the initial 51. The proposed set of features could be used for the classification between the AR and AF signals to assist diagnosis of the mentioned heart diseases. © 2023 IEEE.

关键词： Statistical tests

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Statistical filtering methods for feature selection in arrhythmia classification 29

Statistical filtering methods for feature selection in arrhy...

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29th International Conference on Information, Communication and Automation Technologies, ICAT 2023

作者： Fejzic, Ajdin Tihak, Amina Boskovic, Dusanka University of Sarajevo Faculty of Electrical Engineering Department of Automatic Control and Electronics Sarajevo Bosnia and Herzegovina

ISBN: (纸本)9798350399837

In this study we demonstrate the appropriate use of statistically based filtering methods for feature selection and describe the application to Heart Rate Variability (HRV) features used to distinguish between arrhythmia and normal sinus rhythm electrocardiogram (ECG) signals. The initial set of HRV features is evaluated using both correlation and statistical significance tests. Normality assumption is assessed for each feature in order to select appropriate correlation methods and significance tests. In addition, the impact of outliers on the statistical test results is illustrated by an explorative analysis of correlation before and after outlier removal. Finally, a reduced set of features is selected, and the decision process guided by correlation and statistical significance test results is described and discussed. © 2023 IEEE.

关键词： Feature Selection

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Video quality enhancement using different enhancement and dehazing techniques

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Journal of Ambient Intelligence and Humanized Computing 2023年第12期14卷 16607-16635页

作者： Ayoub, Abeer Naeem, Ensherah A. El-Shafai, Walid El-Samie, Fathi E. Abd Hamad, Ehab K. I. El-Rabaie, El-Sayed M. Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Electrical Department Faculty of Technology and Education Suez University Suez43527 Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Electrical Engineering Department Faculty of Engineering Aswan University Aswan81542 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Video in an outdoor environment suffers from the haze problem due to smoke, dust, and other particles in the atmosphere. The quality of video under these atmospheric conditions is clearly/dramatically degraded, leading to poor contrast and information leakage. The proposed algorithm in this paper depends on pre-processing of video frames prior to the dehazing process. Different enhancement techniques are used to remove noise and control the dynamic range, because each frame has some noise due to sensor measurement errors. This noise might be magnified during the haze removal process, if totally neglected. Previous dehazing algorithms enhance the video contrast and reduce frame degradation. We use optimized dehazing algorithms, namely a dual-transmission-map dehazing algorithm, and a recursive Deep Residual Learning (DRL) network, as dehazing tools. We modify the previous dehazing algorithms to generate new algorithms to be suitable not only for visible frames but also for Near Infrared (NIR) frames. In the optimized dehazing algorithms, the haze effect is reduced, according to the hazing model. In the dual-transmission-map dehazing algorithm, the effect of attenuation parameter R and attenuation weight U on the dehazed frames is investigated. A dual-transmission-map algorithm, depending on the Dark Channel Prior (DCP) technique, is studied. We study the effect of a regularization parameter Ω on the visible and NIR dehazed frames without and with enhancement techniques. For the recursive deep residual learning algorithm, we increase the number of iterations in the DRL network from three iterations in the traditional DRL algorithm without denoising techniques to nine iterations, in order to explore the impact of increasing the number of iterations on the output dehazed frames. Since elapsed time grows with the number of iterations, we terminate the operation after the ninth iteration. A comparison between traditional algorithms and the proposed dehazing algorithms is

关键词： Deep learning

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Trajectory Tracking of the Octo-Rotor Unmanned Aerial Vehicle Exposed to Parametric Uncertainties and External Disturbances Using First Order Sliding Mode control 29

Trajectory Tracking of the Octo-Rotor Unmanned Aerial Vehicl...

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29th International Conference on Information, Communication and Automation Technologies, ICAT 2023

作者： Salihbegovic, Almir Capin, Vedad Sokic, Emir Osmic, Nedim University of Sarajevo Faculty of Electrical Engineering Department for Automatic Control and Electronics Sarajevo Bosnia and Herzegovina

ISBN: (纸本)9798350399837

control design for trajectory tracking of multi-rotor aerial vehicles (MAVs) represents a challenging task due to the under-actuated property, highly nonlinear and cross-coupled dynamics, modeling errors, parametric uncertainties and external disturbances. This paper presents the design of the first order sliding mode control (FOSMC) algorithm for trajectory tracking of the octo-rotor unmanned aerial vehicle (UAV) in the presence of various disturbances. The highly nonlinear octo-rotor UAV dynamics is considered via the generalized framework for MAVs modeling. The stability analysis of the closed-loop system is presented using the Lyapunov based approach. The developed FOSMC exhibits finite-time convergence of the octo-rotor trajec-tories to the sliding manifold and the asymptotic stability of the equilibrium in the presence of vanishing disturbances. Simulation studies show a superior tracking performance and robustness properties of the FOSMC in comparison with the concurrent techniques for trajectory tracking of the octo-rotor UAV in the presence of internal and external disturbances. © 2023 IEEE.

关键词： Sliding mode control

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Production Cost and Emissions Minimization Based on Renewable Energy Using Superiority of Feasible Solutions- Moth Flame Optimization 4

Production Cost and Emissions Minimization Based on Renewabl...

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4th International Conference on Robotics, electrical and Signal Processing Techniques, ICREST 2025

作者： Alam, Mohammad Khurshed Sayem, Shaoran Sulaiman, Mohd Herwan Ferdowsi, Asma Islam, Mishiba Islam, Mohammad Zohurul American International University-Bangladesh Faculty of Electrical & Electronics Engineering Technology Dhaka Bangladesh Faculty of Electrical & Electronics Engineering Technology Pahang Pekan26600 Malaysia Sir Salimullah Medical College Hospital Pharmacology Department Dhaka1206 Bangladesh University of Louisiana at Lafayette Department of Electrical and Computer Engineering LA United States

ISBN: (纸本)9798331530938

This paper introduces a refined version of the Moth Flame Optimization (MFO) algorithm, Superiority of Feasible Solutions-Moth Flame Optimization (SF-MFO), in recognition of the significant influence of renewable energy on both production costs and secretion reduction in energy structure. To improve the symmetry among scrutiny and fleecing also to resolve the limitations of the early MFO, SF-MFO implements two significant enhancements. The algorithm's objective is to reduce emissions and optimize production costs by utilizing renewable energy sources, resulting in a combined reduction in both. Its primary intention is to decrease the total operating expense of the production system, as well as to address active power loss, voltage deviations at load buses, and the cost and emissions of combined units. The SF-MFO is analyse on IEEE 30-bus and IEEE 118-bus structure by transforming this multi-objective problem into a single-objective function with specific constraints and utilizing a bus location index to refine the list of candidate buses. The effectiveness and benefits of the suggested SF-MFO are then highlighted by contrasting the outcomes with those of other published algorithms. © 2025 IEEE.

关键词： Premixed flames

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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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MRI Brain Tumor Classification Using Optimized APSO-LLRBFNN 2

MRI Brain Tumor Classification Using Optimized APSO-LLRBFNN

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2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Krishna, Tiruveedula Gopi Sreenivas, Nune Ajay Kumar, M. Reddy, Chandra Sekhar Rathee, Davinder Sing Urgessa, Teklu College of Electrical Engineering and Computing Adama Science and Technology University Department of Computer Science and Engineering Adama Ethiopia Andhra Loyala institute of Engineering and Technology Department of Electrical and Electronics Engineering Vijayawada India College of Electrical Engineering and Computing Adama Science and Technology University Department of Electrical Power and Control Engineering Adama Ethiopia College of Electrical Engineering and Computing Adama Science and Technology University Department of ECE Adama Ethiopia

ISBN: (纸本)9798331505745

The research presents a new efficient machine learning method to classify brain tumors because this task remains vital in fighting the high incidence of brain cancers. The proposed approach unites all its operations including image segmentation with feature extraction and classification into a single processing system. This study uses Particle Swarm Optimization (PSO) and Adaptive PSO (APSO) methodologies to optimize Locally Linear Radial Basis Function Neural Network (LLRBFNN) resulting in PSO-LLRBFNN and APSO-LLRBFNN model implementations. The research examined the optimized APSO-LLRBFNN models against Support Vector Machines (SVM) and Least Mean Squares (LMS) based LLRBFNN classifier methods. Results from experiments show that APSO-LLRBFNN gives superior outcomes with 98.93% accuracy and takes 12.23 seconds for execution, which surpasses currently available methods. © 2025 IEEE.

关键词： Particle swarm optimization (PSO)

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A Study on 1D-Point Cloud Using Through-Wall mm Wave Radar for Human Pose Estimation 12

A Study on 1D-Point Cloud Using Through-Wall mm Wave Radar f...

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12th International electrical engineering Congress, iEECON 2024

作者： Phaisiri, Kritthee Kittiyanpunya, Chainarong Shutimarrungson, Nattakarn Boonpoonga, Akkarat Akkaraekthalin, Prayoot Kaemarungsi, Kamol King Mongkut's University Of Technology North Bangkok Faculty Of Engineering Department Of Electrical And Computer Engineering Bangkok Thailand Rajamangala University Of Technology Rattanakosin Faculty Of Engineering Department Of Mechatronics Engineering Nakhon Pathom Thailand Mahasarakham Business School Mahasarakham University Department Of Business Computer Maha Sarakham Thailand Faculty Of Engineering Department Of Electrical And Computer Engineering Bangkok Thailand National Electronics And Computer Technology Center National Science And Technology Development Agency Pathum Thani Thailand

ISBN: (纸本)9798350383591

This paper presents human pose estimation using millimeter-wave (mmWave) radar technology capable of penetrating obstacles. Operating within the frequency modulated continuous wave (FMCW) at 60 - 64 GHz, our radar system generates signals conducive to accurate human pose representation. Our data processing framework focuses on producing point cloud data, effectively capturing each human movement. Results are visualized through a 2D graph, with the z-axis representing time. Experimental data, collected from various activities conducted behind different walls, underwent thorough analysis, comparing point cloud positions with actual human postures. The outcomes affirm the effectiveness of mmWave radar systems, positioned behind obstacles, in accurately extracting human postures. © 2024 IEEE.

关键词： Frequency modulation

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