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Wireless modulation classification based on Radon transform and convolutional neural networks

Journal of Ambient Intelligence and Humanized Computing 2023年第5期14卷 6263-6272页

作者： Ghanem, Hanan S. Al-Makhlasawy, Rasha M. El-Shafai, Walid Elsabrouty, Maha Hamed, Hesham F. A. Salama, Gerges M. El-Samie, Fathi E. Abd Department of Electrical Engineering Faculty of Engineering Minia University Minia61111 Egypt Department of Computers and Systems Electronics Research Institute Cairo Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Electronics and Communications Engineering Egypt-Japan University of Science and Technology Alexandria Egypt Faculty of Engineering Egyptian-Russian University Cairo Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Convolutional Neural Networks (CNNs) are efficient tools for pattern recognition applications. They have found applications in wireless communication systems such as modulation classification from constellation diagrams. Unfortunately, noisy channels may render the constellation points deformed and scattered, which makes the classification a difficult task. This paper presents an efficient modulation classification algorithm based on CNNs. Constellation diagrams are generated for each modulation type and used for training and testing of the CNNs. The proposed work depends on the application of Radon Transform (RT) to generate more representative patterns for the constellation diagrams to be used for training and testing. The RT has a good ability to represent discrete points in the spatial domain as curved lines. Several pre-trained networks including AlexNet, VGG-16, and VGG-19 are used as classifiers for modulation type from the spatial-domain constellation diagrams or their RTs. Several simulation experiments are presented in this paper to compare different scenarios for modulation classification at different Signal-to-Noise Ratios (SNRs) and fading channel conditions. © 2022, The Author(s).

关键词： Fading channels

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Deep Transfer Learning Models for Mobile-Based Ocular Disorder Identification on Retinal Images

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computers, Materials & Continua 2024年第7期80卷 139-161页

作者： Roseline Oluwaseun Ogundokun Joseph Bamidele Awotunde Hakeem Babalola Akande Cheng-Chi Lee Agbotiname Lucky Imoize Department of Multimedia Engineering Kaunas University of TechnologyKaunas44249Lithuania Department of Computer Science Landmark UniversityOmu Aran251103Nigeria Department of Computer Science Faculty of Information and Communication SciencesUniversity of IlorinIlorin240003Nigeria Department of Telecommunication Science University of IlorinIlorin230003Nigeria Department of Library and Information Science Fu Jen Catholic UniversityNew Taipei City24205TaiwanChina Department of Computer Science and Information Engineering Fintech and Blockchain Research CenterAsia UniversityTaichung City41354TaiwanChina Department of Electrical and Electronics Engineering Faculty of EngineeringUniversity of LagosAkokaLagos100213Nigeria Department of Electrical Engineering and Information Technology Institute of Digital CommunicationRuhr UniversityBochum44801Germany

Mobile technology is developing *** phone technologies have been integrated into the healthcare industry to help medical ***,computer vision models focus on image detection and classification ***2 is a computer vision model that performs well on mobile devices,but it requires cloud services to process biometric image information and provide predictions to *** leads to increased *** biometrics image datasets on mobile devices will make the prediction faster,but mobiles are resource-restricted devices in terms of storage,power,and computational ***,a model that is small in size,efficient,and has good prediction quality for biometrics image classification problems is *** pre-trained CNN(PCNN)MobileNetV2 architecture combined with a Support Vector Machine(SVM)compacts the model representation and reduces the computational cost and memory *** proposed novel approach combines quantized pre-trained CNN(PCNN)MobileNetV2 architecture with a Support Vector Machine(SVM)to represent models efficiently with low computational cost and *** contributions include evaluating three CNN models for ocular disease identification in transfer learning and deep feature plus SVM approaches,showing the superiority of deep features from MobileNetV2 and SVM classification models,comparing traditional methods,exploring six ocular diseases and normal classification with 20,111 images postdata augmentation,and reducing the number of trainable *** model is trained on ocular disorder retinal fundus image datasets according to the severity of six age-related macular degeneration(AMD),one of the most common eye illnesses,Cataract,Diabetes,Glaucoma,Hypertension,andMyopia with one class *** the experiment outcomes,it is observed that the suggested MobileNetV2-SVM model size is *** testing accuracy for MobileNetV2-SVM,InceptionV3,and MobileNetV2 is 90.11%,86.88%,a

关键词： Retinal images ocular disorder deep transfer learning disease identification mobile device

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Wide-Angle Scanning Antennas for Millimeter-Wave 5G Applications

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engineering 2022年第4期8卷 60-71页

作者： Raj Mittra Abdelkhalek Nasri Ravi Kumar Arya Electrical and Computer Engineering University of Central FloridaOrlandoFL 32816USA Electrical and Computer Engineering Department Faculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Electronics and Communication Engineering National Institute of Technology DelhiDelhi 110040India

The fifth generation(5G)network communication systems operate in the millimeter waves and are expected to provide a much higher data rate in the multi-gigabit range,which is impossible to achieve using current wireless services,including the sub-6 GHz *** this work,we briefly review several existing designs of millimeter-wave phased arrays for 5G applications,beginning with the low-profile antenna array designs that either are fixed beam or scan the beam only in one *** then move on to array systems that offer two-dimensional(2D)scan capability,which is highly desirable for a majority of 5G ***,in the main body of the paper,we discuss two different strategies for designing scanning arrays,both of which circumvent the use of conventional phase shifters to achieve beam *** note that it is highly desirable to search for alternatives to conventional phase shifters in the millimeter-wave range because legacy phase shifters are both lossy and costly;furthermore,alternatives such as active phase shifters,which include radio frequency amplifiers,are both expensive and *** this backdrop,we propose two different antenna systems with potential for the desired 2D scan performance in the millimeter-wave *** first of these is a Luneburg lens,which is excited either by a 2D waveguide array or by a microstrip patch antenna array to realize 2D scan ***,for second design,we turn to phased-array designs in which the conventional phase shifter is replaced by switchable PIN diodes or varactor diodes,inserted between radiating slots in a waveguide to provide the desired phase shifts for ***,we discuss several approaches to enhance the gain of the array by modifying the conventional array *** describe novel techniques for realizing both one-dimensional(1D)and 2D scans by using a reconfigurable metasurface type of panels.

关键词： Luneburg lens Scanning arrays Millimeter-wave antennas Switchable phase shifters Reconfigurable metasurfaces

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Toward Realization of RIS-assisted Wireless Information and Power Transfer System: Implementation and Experiments

Toward Realization of RIS-assisted Wireless Information and ...

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2024 International Symposium on Antennas and Propagation, ISAP 2024

作者： Park, Je Hyeon Amri, Muhammad Miftahul Tran, Nguyen Minh Cho, Sung Woo Kim, Su Hyun Lee, Jina Kim, Dong In Choi, Kae Won Department of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of Faculty of Electronics and Telecommunications VNU - University of Engineering and Technology Hanoi Viet Nam

ISBN: (纸本)9798350364774

This paper presents a series of studies on the implementation of reconfigurable intelligent surface (RIS) in wireless communication and power transfer systems. The discussed studies put together comprehensive RIS-assisted systems covering RIS unit cell design, testbed setup, practical algorithms, and experimental validations. The results of these experiments highlight the significant enhancement that RIS can bring to wireless network performance. © 2024 IEEE.

关键词： Inductive power transmission

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Lightweight and Roubust Key Agreement for Securing IIoT-Driven Flexible Manufacturing Systems

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IEEE Internet of Things Journal 2025年第11期12卷 17197-17209页

作者： Hammad, Muhammad Badshah, Akhtar Almeer, Mohammed A. Waqas, Muhammad Song, Houbing Chen, Sheng Han, Zhu GIK Institute of Engineering Sciences and Technology Faculty of Mechanical Engineering Topi23640 Pakistan University of Malakand Department of Software Engineering Dir Lower18800 Pakistan University of Bahrain Computer Engineering Department College of Information Technology 32038 Bahrain University of Greenwich Faculty of Engineering and Science Centre for Sustainable Cybersecurity United Kingdom Edith Cowan University School of Engineering PerthWA6027 Australia Department of Information Systems BaltimoreMD United States University of Southampton School of Electronics and Computer Science SouthamptonSO17 1BJ United Kingdom University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

The ever-evolving Internet of Things (IoT) has ushered in a new era of intelligent manufacturing across multiple industries. However, the security and privacy of real-time data transmitted over the public channel of the industrial IoT (IIoT) remain formidable challenges. Existing lightweight protocols often omit one or more critical security features, such as anonymity and untraceability, and are susceptible to threats like desynchronization attacks. Additionally, they struggle to achieve an optimal balance between robust security and performance efficiency. To bridge these gaps, we introduce a new lightweight key agreement security scheme that guarantees secure access to the IIoT-enabled flexible manufacturing system (FMS). The strength of our scheme lies in its utilization of the authenticated encryption with associative data (AEAD) primitive, AEGIS, along with hash functions and physical unclonable functions, which secure the IIoT ecosystem. Additionally, our scheme offers flexibility in the form of the addition of new machines, password updates, and revocation in cases of theft or loss. A comprehensive security analysis demonstrates the efficacy of the proposed scheme in thwarting various attacks. The formal analysis, based on the Real-Or-Random (RoR) model, ensures session key indistinguishability, while the informal analysis highlights its resilience against known attacks. The comparative assessment demonstrate that the proposed scheme consistently outperforms the benchmark schemes across multiple dimensions, including security and functionality features, computational and communication overheads, and runtime efficiency. Specifically, the proposed scheme achieves peak performance enhancements of 77.55%, 44.73%, and 69.6% in computational overhead, runtime overhead, and communication overhead, respectively, underscoring its substantial performance advantages. © 2025 IEEE.

关键词： Flexible manufacturing systems

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Enhancing Cyber-Physical Threat Assessment in Power Distribution Networks. 11

Enhancing Cyber-Physical Threat Assessment in Power Distribu...

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11th International Conference on ENERGY and ENVIRONMENT, CIEM 2023

作者： Alasali, Feras AlMajali, Anas Abudayyeh, Mohammad Aldeiri, Bashar El-Naily, Naser Zarour, Eyad Department of Electrical Engineering Faculty of Engineering The Hashemite University. Zarqa Jordan Department of Computer Engineering Faculty of Engineering The Hashemite University Zarqa Jordan college of Electrical and Electronics Technology Benghazi Libya Electrical Engineering Department The University of Jordan Amman Jordan

ISBN: (纸本)9798350340785

—The existing literature on cyber-physical threat investigations predominantly concentrates on the high voltage (HV) level, disregarding the higher probability of cyber-attacks and threats targeting low voltage (LV) networks. In the context of smart grids, where millions of interconnected electronic devices span from power generation units to customer interface units through communication networks, the reliability of electrical infrastructure and information security face immediate challenges. This research aims to fill this gap by tracing the impact of various cyber-physical threat scenarios on a realistic LV power distribution network, utilizing simulations conducted with ETAP. Furthermore, this work will present a comprehensive risk assessment of the consequences of cyber-attacks on LV networks, encompassing distributed Energy Resources (DERs). The inclusion of DERs and smart components introduces security vulnerabilities through their remote control and communication capabilities. Although the impact of cyber-attacks on LV networks, typically leading to localized power outages, has received limited investigation, the potential for national consequences remains largely unexplored, especially when a cyber-attack targets a microgrid system. The findings will contribute to the improvement of smart grid systems, and response mechanisms against ongoing attacks. ©2023 IEEE.

关键词： Smart power grids

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Texture Analysis of Breast US Images Using Morphological Transforms, Hausdorff Dimension and Bagging Ensemble Method 32

Texture Analysis of Breast US Images Using Morphological Tra...

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32nd Mediterranean Conference on control and Automation, MED 2024

作者： Tabacaru, Gigi Moldovanu, Simona Barbu, Marian 'Dunarea de Jos' University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Automatic Control and Electrical Engineering Romania 'Dunarea de Jos' University of Galati Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Romania Dunarea de Jos University of Galati The Modelling & Simulation Laboratory Galati800008 Romania

ISBN: (纸本)9798350395440

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer. © 2024 IEEE.

关键词： Fractal dimension

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A Modified Dempster Shafer Approach to Classification in Surgical Skill Assessment 31

A Modified Dempster Shafer Approach to Classification in Sur...

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31st International Conference on electrical engineering, ICEE 2023

作者： Iranfar, Arash Soleymannejad, Mohammad Moshiri, Behzad Taghirad, Hamid D. School of Electrical and Computer Engineering University College of Engineering University of Tehran Tehran Iran University of Waterloo Department of Electrical and Computer Engineering Waterloo Canada Industrial Control Center of Excellence Faculty of Electrical Engineering Tehran Iran

ISBN: (纸本)9798350312560

Artificial intelligence systems are usually implemented either using machine learning or expert systems. Machine learning methods are usually more accurate and applicable to a broader range of applications. Expert systems, on the other hand, require much less data for training and generate more comprehensible results. These characteristics are typically desired in the fields of surgery and medicine because there isn't much data available. In order to give a machine's decisions a deeper level of semantics, it is also advantageous to incorporate a doctor's expertise into it. Furthermore, it is safer to understand the reasoning behind a machine's choices. In this paper, a Dempster-Shafer Theory (DST) based expert system is suggested for the task of surgical training skill assessment. An interval-based probabilistic feature analysis was applied to the data to assign values to the mass functions. Zhang's rule of combination was applied to handle the conflicting evidence in the prediction phase. The performance of the proposed method was compared to another DST classifier, SVM, and XGBoost. Our method outperforms SVM and other DST classifiers, but it is not as precise as XGBoost. By reducing the size of the dataset, the added benefit of using an expert system as opposed to a machine learning method was explored further. The performance of the suggested method is not adversely affected by the size of the dataset, whereas the XGBoost classifier is. © 2023 IEEE.

关键词： Classification (of information)

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Studying Physical Properties of Gas-To-Liquid Compared with Mineral Oil under Accelerated Thermal Aging 25

Studying Physical Properties of Gas-To-Liquid Compared with ...

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25th International Middle East Power System Conference, MEPCON 2024

作者： Badawi, Mohamed Ibrahim, Shimaa A. Mansour, Diaa-Eldin A. El-Faraskoury, Adel Ward, Sayed A. Benha University Faculty of Engineering at Shoubra Department of Electrical Engineering Egypt Egypt-Japan University of Science and Technology School of Electronics Communications and Computer Engineering Electrical Power Engineering Department Alexandria Egypt Tanta University Faculty of Engineering Electrical Power and Machines Engineering Department Tanta Egypt Egyptian Electricity Holding Company Extra High Voltage Research Centre Egypt Delta University for Science and Technology Faculty of Engineering Department of Electrical Engineering Egypt

ISBN: (纸本)9798350379648

Mineral oil (MO) has long been utilized in high-voltage power transformers, as a cooling and dielectric medium;because of it is availability as it is extracted from fossil oil. Recently, Gas-To-Liquid (GTL) has a significant increase in use due to its superior performance, its purity and chemical consistency over conventional mineral oils. This paper presents examination of the temperature effects on mineral (Diala S2) and gas to liquid (Diala S4) oil physical properties. Fresh oil and aged oil samples, of the two oil types, have been tested in this paper. Accelerated thermal aging test have been conducted in laboratory to simulate the heat stress experienced by transformers during operation. Three aged oil samples, of the two types of oil, have been prepared in laboratory (3, 6, and 10 days). Density and viscosity measurements were performed on these fresh and aged oil samples. The results concluded that during the initial years, chemical changes cause a minor drop in the density of the mineral oil. Conversely, GTL oil has superior qualities since it stays more stable over time. Over time, the density of both oils exhibits comparable stability, however GTL oil is favored over mineral oil due to its consistency and stability. Diala S4 and Diala S2 oils have higher viscosity, suggesting superior cooling performance before aging. However, Diala S2 dropped to 10.649 mm2/s after three years, indicating its long-term consequences. Diala S4 oil had higher flow efficiency, enhancing transformer cooling and insulating performance within thermal aging. This is due to GTL oil, derived from natural gas, has higher resistance to chemical deterioration, allowing it to sustain its viscosity stability over extended periods. These results emphasize the importance of choosing oils, especially GTL oil type based on their apparent and physical stability over time. © 2024 IEEE.

关键词： Viscosity

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Impact of different voltage source models on antenna current and input impedance within the boundary element method formalism 24

Impact of different voltage source models on antenna current...

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24th International Conference on Applied Electromagnetics and Communications, ICECOM 2023

作者： Susnjara, Anna Poljak, Dragan University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Department of Electronics and Computer Science Split Croatia

ISBN: (纸本)9798350313017

This paper investigates the differences in dipole current and input impedance due to different source models in the framework of boundary element formalism. The half-wavelength and full-wavelength dipole antennas are placed in free space and above a lossy medium. Antenna current and input impedance are obtained by numerically solving the Pocklington's integro-differential equation via Galerkin-Bubnov Indirect Boundary Element Method (GB-IBEM). Two different feeding structures are used as excitation sources, a delta gap source model usually used under GB-IBEM formalism and a magnetic frill source model. Different segment numbers are also used. The results indicate that the current magnitude in case of half-wavelength dipole antenna varies to a relatively great extent depending on the applied voltage generator model. Input impedance does not vary due to different source models, however, its value changes greatly with segment number. © 2023 IEEE.

关键词： Boundary element method

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