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electronic engineering (ICEEM), International Conference on

作者： Ahmed A. Mageed Samah Abdel Aziz Ayman El-Sayed Talaat Abdelhamid Computer Science and Engineering Faculty of Electronic Engineering Menoufiya University Egypt Faculty of Science Zagazig University Zagazig Egypt Physics and Mathematical Engineering Faculty of Electronic Engineering Menoufia University Menoufia Egypt

Skin cancer is a significant public health concern, necessitating accurate and timely detection for effective treatment. Deep learning models have emerged as promising tools for skin cancer classification, demonstrating remarkable accuracy in various studies. However, the performance of deep learning models heavily relies on the choice of optimizer, which affects the training process and convergence speed. In this paper, we investigate the accuracy variance between different optimizers in deep learning models for skin cancer classification. Different deep learning architectures, such as convolutional neural networks (CNNs) are implemented on HAM 10000 (Human Against Machine) dataset to train the skin cancer classification models. The obtained results compare different optimizers such as Root Mean Square Propagation (RMSProp), Nadam, AdaDelta, Stochastic Gradient Descent (SGD), Adamax, Adagrad, Adam, and Adam-M, in terms of the model accuracy. As a future direction we recommend hybrid techniques and modifications of Adam technique.

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Fourth-Order Cumulant Based 3-D Near-Field Underdetermined Parameter Estimation With Exact Spatial Propagation Model

Fourth-Order Cumulant Based 3-D Near-Field Underdetermined P...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Longsheng Jin Hua Chen Jiaxiong Fang Wei Liu Ye Tian Gang Wang Faculty of Electrical Engineering and Computer Science Ningbo University China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Based on the exact spherical wavefront model, an under-determined estimation method for three-dimensional (3-D) parameters of near-field (NF) sources using L-shaped nested arrays is proposed, referred to as the cumulant algorithm. This algorithm leverages the temporal-spatial domain cumulants of NF sources by constructing virtual data through delayed fourth-order cumulant (FOC) calculations of the original received data. Subsequently, a spatial-spectrum-based subspace method is applied for 3-D NF localization, which involves a 3-D spectral search procedure. Additionally, the maximum number of identifiable NF sources of the proposed algorithm is analyzed. Simulation results demonstrate that, based on the exact spherical wavefront model, the proposed algorithm can achieve underdetermined 3-D parameter estimation of NF sources without any matching process, and it performs better in localization than existing methods.

关键词： Location awareness Solid modeling Three-dimensional displays Parameter estimation Simulation Signal processing algorithms Estimation Approximation algorithms Noise measurement Speech processing

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A Near-Field 3D Parameter Estimation Method Based on a Symmetric Enhanced Nested Array

A Near-Field 3D Parameter Estimation Method Based on a Symme...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Linke Yu Hua Chen Dingfan Xue Wei Liu Ye Tian Gang Wang Faculty of Electrical Engineering and Computer Science Ningbo University China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In this paper, a high-precision three-dimensional (3-D) near-field (NF) localization method is proposed under an underdetermined case based on a symmetric enhanced nested array (SENA). Firstly, the symmetry of the array and the fourth-order cumulant (FOC) are utilized to construct the equivalent virtual far-field (FF) reception data. Then, a gridless sparse and parametric approach (SPA), combined with an l 1 -SVD based pairing procedure, is used to obtain estimates for two paired angles. Finally, a one-dimensional (1-D) spectral estimator is applied to obtain the estimate of range parameter. Simulation results show the effectiveness of the proposed method.

关键词： Location awareness Three-dimensional displays Parameter estimation Simulation Signal processing algorithms Estimation Reconstruction algorithms Multiple signal classification Arrays Speech processing

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Estimation Large-Scale Fading Channels for Transmit Orthogonal Pilot Reuse Sequences in Massive MIMO System

Estimation Large-Scale Fading Channels for Transmit Orthogon...

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2022 International Conference on Intelligent Technology, System and Service for Internet of Everything, ITSS-IoE 2022

作者： Abdullah, Qazwan Shah, Nor Shahida Mohd Hamzah, Shipun Salh, Adeb Mohamad, Mahathir Nordin, Shahilah Abu, Maisarah Albaom, Mohammed Abdo Sadeq, Safwan Community College of Yareem Ibb Yemen Universiti Tun Hussein Faculty of Engineering Technology Johor Malaysia Universiti Tun Hussein Faculty of Electrical and Electronic Engineering Johor Malaysia Universiti Tun Hussein Faculty of Applied Sciences and Technology Johor Malaysia Malaysia Faculty of Electrical Engineering Pulau Pinang Malaysia University Technical Malaysia Malacca Faculty of Electronic and Computer Engineering Malacca Malacca City Malaysia Universiti Putra Serdang Faculty of Computer Science and Information Technology Department of Computer Science Malaysia Universiti Teknologi Petronas Department of Mechanical Engineering Perak Malaysia

ISBN: (数字)9781665459983

ISBN: (纸本)9781665459983

Massive multiple-input multiple-output (MIMO) is a critical technology for future fifth-generation (5G) systems. Reduced pilot contamination (PC) enhanced system performance, and reduced inter-cell interference and improved channel estimation. However, because the pilot sequence transmitted by users in a single cell to neighboring cells is not orthogonal, massive MIMO systems are still constrained. We propose channel evaluation using orthogonal pilot reuse sequences (PRS) and zero forced (ZF) pre-coding techniques to eliminate channel quality in end users with poor channel quality based on channel evaluation, large-scale shutdown evaluation, and analysis of maximum transmission efficiency. We derived the lower bounds on the downlink data rate (DR) and signal-to-interference noise ratio (SINR) that can be achieved based on PRS assignment to a group of users where the number of antenna elements mitigated the interference when the number of antennas reaches infinity. The channel coherence interval limitation, the orthogonal PRS cannot be allocated to all UEs in each cell. The short coherence intervals able to reduce the PC and improve the quality of channel. The results of the modelling showed that higher DR can be achieved due to better channel evaluation and lower loss. © 2022 IEEE.

关键词： Fading channels

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Orthogonal matrix of polarization combinations:concept and application to multichannel holographic recording

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Opto-electronic Advances 2024年第10期7卷 4-13页

作者： Shujun Zheng Jiaren Tan Hongjie Liu Xiao Lin Yusuke Saita Takanori Nomura Xiaodi Tan Information Photonics Research Center College of Photonic and Electronic EngineeringFujian Normal UniversityFuzhou 350117China Department of Electrical and Computer Engineering Duke UniversityDurhamNC 27708USA College of Photonic and Electronic Engineering Key Laboratory of Opto-Electronic Science and for Medicine of Ministry of EducationFujian Provincial Key Laboratory of Photonics TechnologyFujian Provincial Engineering Technology Research Center of Photoelectric Sensing ApplicationFujian Normal UniversityFuzhou 350117China Faculty of Systems Engineering Wakayama University930 SakaedaniWakayama640-8510Japan.

Orthogonal matrices have become a vital means for coding and signal processing owing to their unique distributional *** orthogonal matrices based on amplitude or phase combinations have been extensively explored,the orthogonal matrix of polarization combinations(OMPC)is a novel,relatively unexplored ***,we propose a method for constructing OMPCs of any dimension encompassing 4n(where n is 1,2,4,8,…)mutually orthogonal 2ncomponent polarization *** the field of holography,the integration of polarization multiplexing techniques with polarization-sensitive materials is expected to emerge as a groundbreaking approach for multichannel hologram multiplexing,offering considerable enhancements in data storage capacity and security.A multidimensional OMPC enables the realization of multichannel multiplexing and dynamical modulation of information in polarization holographic *** consolidating all information into a single position within the material,we effectively avoided extraneous crosstalk during the reconstruction *** results show that achieving four distinct holographic images individually and simultaneously depends on the polarization combination represented by the incident *** discovery opens up a new avenue for achieving highly holographic information storage and dynamically displayed information,harnessing the potential of OMPC to expand the heretofore limited dimensionality of orthogonal polarization.

关键词： orthogonal matrix of polarization combinations polarization-modulated multiplexing multichannel recording polarization holography dynamical information modulation

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Genetic Algorithm-Based Feature Selection for Accurate Breast Cancer Classification

Genetic Algorithm-Based Feature Selection for Accurate Breas...

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2023 International Conference on IT and Industrial Technologies, ICIT 2023

作者： Shabbir, Attia Ali, Raja Hashim Shabbir, Muhammad Zeeshan Abideen, Zain Ul Khan, Talha Ali Ijaz, Ali Zeeshan Ali, Nisar Imad, Muhammad Bakar, Muhammad Abu Gik Institute of Engg. Sciences & Technology Faculty of Computer Science & Engineering Topi Pakistan University of Europe for Applied Sciences Dept. of Technology & Software Engineering Berlin Germany Department of Electrical Engineering Lahore Pakistan BCMaterials Basque Center for Materials Applications & Nanostructure Basque Country Leioa Spain University of Regina Faculty of Electronic Systems Engineering Regina Canada

ISBN: (纸本)9798350315974

Breast cancer is a significant global healthcare challenge, particularly in developing and underdeveloped countries, with profound physical, emotional, and psychological consequences, including mortality. Timely diagnosis and accurate treatment are crucial in addressing this issue. We propose the utilization of a feature selection technique to identify the most relevant features from among all features for breast cancer diagnosis, and show that Genetic Algorithms are impressive for this task. The study compares the results of GA with no selection and an alternative method, Principle Component Analysis (PCA). Three machine learning models, all based on supervised learning with data split into training and test data, are employed for binary classification using the selected feature subset. The evaluation metrics employed encompass accuracy, precision, recall, and F1-score. Among the selected models, Random Forest demonstrates the most favorable outcomes, achieving an accuracy score of 0.96, precision score of 0.96, recall value of 0.98, and an F1-score of 0.97. These results underscore the effectiveness of GA in feature selection for breast cancer diagnosis. Consequently, the integration of Genetic Algorithms (GA) with Random Forest showcases the superior performance among the evaluated models. © 2023 IEEE.

关键词： Genetic algorithms

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A Review Paper on Face Recognition Techniques 9

A Review Paper on Face Recognition Techniques

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9th International Conference on Advanced Computing and Communication Systems, ICACCS 2023

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

ISBN: (纸本)9798350397376

The study of computer vision and pattern recognition is growing because of the various commercial and practical applications of these disciplines. Identification of individuals in a multitude, access control, forensics, and human-computer interactions are only among the topics studied by these areas. However, analyzing unconstrained face recognition poses ethical issues and privacy concerns. Many recent proposals employ Holistic Methods, Geometric Approach and Local-Texture Approach, methods and databases like ORL, FERET and AR Dataset to study constrained face recognition. At least some understanding of 2D perspective was achieved. This occurred in highly controlled environments where parameters such as camera angles, lighting and distance were strictly regulated. However, significant degradation in recognition performance occurred if the environment changed or the subject smiled or frowned. This critique discusses the technology utilized in face recognition, as well as the databases of methods that utilize this technology. To help guide future research, this article discusses current knowledge and suggests future directions for study in the field of facial recognition. © 2023 IEEE.

关键词： Face recognition

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Stereo ORB-SLAM3 Underwater Performance Evaluation

Stereo ORB-SLAM3 Underwater Performance Evaluation

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Electrical engineering (ICEENG), International Conference on

作者： Hossam Elkeshky Samer A. Mohamed Mohammed I. Awad Hossam Abd El Munim Mechatronics Engineering Dept. Faculty of Engineering Ain Shams University Cairo Egypt Electrical and Electronic Engineering Dept. Faculty of Engineering and Design University of Bath Bath UK Computer Systems and Engineering Dept. Faculty of Engineering Ain Shams University Cairo Egypt

ISBN: (数字)9798331519018

ISBN: (纸本)9798331519025

Site exploration and navigation missions in hazardous locations are examples of the widespread applications of autonomous mobile robots. Efficient simultaneous localization and mapping (SLAM) is essential for the functionality of such robots. Visual SLAM (VSLAM) has become a cost-effective and attractive solution for all types of vehicles in the field. ORB-SLAM3 and its preceding versions are prevailing visual SLAM algorithms in recent literature. ORB-SLAM3 builds a three-dimensional map based on images and supplies a continuous estimate of the vehicle’s pose. This paper demonstrates an experimental evaluation of stereo ORB-SLAM3 performance in scenes with diverse backgrounds. Online ORB-SLAM3 is tested in multiple aerial and underwater environments. The performance of the algorithm is evaluated by comparing against ground-truth estimates provided by offline structure-from-motion techniques. Results show that ORB-SLAM3 can function in structured environments providing acceptable accuracy and satisfactory performance given the right conditions. The algorithm achieves average standard deviation values of 4 cm in underwater scenes depending on the complexity of the followed trajectory.

关键词： Visualization Simultaneous localization and mapping Accuracy Three-dimensional displays Structure from motion Pose estimation Trajectory Complexity theory State estimation Standards

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A New Perspective on Time and Gravity

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Journal of High Energy Physics, Gravitation and Cosmology 2024年第1期10卷 346-362页

作者： Ittipat Roopkom Wirote Jongchanachavawat Chermdhong Prattanaruk Kwanchai Nanan Pichet Wisartpong Thawatchai Mayteevarunyoo Paramote Wardkein Faculty of Engineering and Industrial Technology Phetchaburi Rajabhat University Phetchaburi Thailand School of Electrical and Electronic Engineering Mahanakorn University of Technology Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering Naresuan University Phitsanulok Thailand Department of Telecommunications Engineering School of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

This paper presents a hypothesis regarding the existence of time fused in spacetime, assuming that time possesses the properties of both a particle and a field. This duality is referred to as the field-particle of time (FPT). The analysis shows that when the FPT moves through matter, it causes time dilation. The FPT is also a significant element that appears in relativistic kinetic energy (KE = (γ - 1) · mc²). Accelerating matter to near the speed of light requires relativistic energy approaching infinity, which corresponds to the relativistic kinetic energy. Meanwhile, the potential energy (PE = mc²) from the rest mass remains constant. Then, the mass-energy equation can be rearranged in terms of PE and KE, as shown in E = (1 + (γ - 1)) · mc². The relativistic energy of the FPT also directly affects the gravitational attraction of matter. It transfers energy to each other through spacetime. The analysis demonstrates that the gravitational force is inversely proportional to the distance squared, following Newton’s law of gravity, and it varies with the relative velocity of matter. The relationship equation between relative time and the gravitational constant indicates that a higher intensity of the gravitational field leads to a slower reference time for matter, in accordance with the general theory of relativity. A thought experiment presents a comparison of two atomic clocks placed in different locations. The first one is placed in a room temperature, around 25°C, on the surface of the Earth, and the second one is placed in high-density areas. The analysis, considering the presence of the FPT, shows that the reference time slows down in high-density areas. Therefore, the second clock must be noticeably slower than the first one, indicating the existence of the FPT passing through both atomic clocks at different speeds.

关键词： Field-Particle of Time (FPT) Reference Time Relativistic Mass and Energy of FPT Gravity

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Comparison between Machine Learning Classifier Based On Face Recognition

Comparison between Machine Learning Classifier Based On Face...

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2023 IEEE Renewable Energy and Sustainable E-Mobility Conference, RESEM 2023

ISBN: (纸本)9798350311327

With face recognition, machine learning is one of the computer sciences fields that is getting bigger the quickest. The goal of this study is to give a basic overview of machine learning and the algorithmic paradigms it provides. The study gives a detailed explanation of the basic ideas behind machine learning and the math that turns these ideas into methodologies that can be used in the real world, and discusses and compares the performance of various face recognition methods. Machine learning, a field of AI, has emerged as an important part of the digitizing approaches that have attracted a lot of interest. The purpose of this work is to provide a high-level overview of several of the most widely utilized and commonly used algorithmic techniques for machine learning currently available. The goal of this work is to help readers make educated decisions about the best algorithm for machine learning they should employ for a given task by highlighting the benefits and drawbacks of each method from an implementation point of view. © 2023 IEEE.

关键词： Decision trees

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