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16th UK-Europe-China Workshop on Millimetre Waves and Terahertz Technologies, UCMMT 2023

作者： Zhaoting, Zhong Cheong, Pedro Choi, Wai-Wa University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering 999078 China

ISBN: (纸本)9798350339406

Six-port interferometric receiver is a competitive low-power front-end receive solution and suitable for multi-function wireless applications. In this paper, we propose the wideband, high throughput, concurrent dual-band receiver based on six-port interferometric technique. A wideband receiver is operated as dual-band operation in 3.4 GHz and 3.8 GHz respectively. A single LO at 3.6 GHz is fed to this six-port interferometric receiver and thus it is capable to achieve wide bandwidth up to 100 MHz. Various high throughput for OFDM signals are transmitted and received by the proposed six-port concurrent dual-band receiver under concurrent dual-band operations. Based on the experimental results for different modulation settings, the receiver achieves error vector magnitude (EVM) as low as 3.7% in single band operation whilst EVM no higher than 4.9% for all channels under dual wideband concurrent operation. These meets the modern high-speed communication's need. © 2023 IEEE.

关键词： Orthogonal frequency division multiplexing

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A Vertically-Polarized End-Fire Leaky Wave Antenna with High Gain and Improved Efficiency

A Vertically-Polarized End-Fire Leaky Wave Antenna with High...

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2023 International Applied Computational Electromagnetics Society Symposium, ACES-China 2023

作者： Duan, Junbing Zhu, Lei Faculty of Science and Technology University of Macau Taipa Department of Electrical and Computer Engineering China

ISBN: (纸本)9781733509657

This paper introduces a recently proposed end-fire leaky wave antenna (LWA) with high radiation gain and efficiency under vertical polarization. By periodically loading a series of shorting-pins in the double-sided-parallel-strip-line (DSPSL), a leakage region as well as end-fire radiation condition point can be generated on the fundamental mode of transmission line with normalized phase constant equal to 1. In order to enhance the radiation efficiency of the pin-loaded LWA, the U-shaped slots are etched at the vicinity of pins on the two surfaces of DSPSL to enlarge the attenuation constant values in the end-fire operation frequency range. Hence, the high end-fire gain with high efficiency can be realized on a compact structure with a limited antenna length. A prototype is designed in final, where the good agreement between simulated and measured results confirms the predicted performances of the proposed end-fire LWA. © 2023 Applied Computational Electromagnetics Society (ACES).

关键词： Radiation efficiency

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Isolation Enhancement in a Compact Four-Element MIMO Antenna for Ultra-Wideband Applications

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computers, Materials & Continua 2023年第4期75卷 911-925页

作者： Awais Khan Shahid Bashir Salman Ghafoor Hatem Rmili Jawad Mirza Ammar Ahmad Department of Electrical Engineering University of Engineering and TechnologyPeshawar25000Pakistan Department of Electrical Engineering University of Science and TechnologyBannu28100Pakistan School of Electrical Engineering and Computer Science(SEECS) National University of Sciences and Technology(NUST)Islamabad44000Pakistan Electrical and Computer Engineering Department Faculty of EngineeringKing Abdulaziz UniversityJeddahSaudi Arabia K.A.CARE Energy Research and Innovation Center King Abdulaziz UniversityJeddah21589Saudi Arabia SEECS Photonic Research Group National University of Sciences and TechnologyIslamabad44000Pakistan

Mutual coupling reduction or isolation enhancement in antenna arrays is an important area of research as it severely affects the performance of an *** this paper,a new type of compact and highly isolated Multiple-Input-Multiple-Output(MIMO)antenna for ultra-wideband(UWB)applications is *** design consists of four radiators that are orthogonally positioned and confined to a compact 40×40×0.8 mm3 *** final antenna design uses an inverted L shape partial ground to produce an acceptable reflection coefficient(S11<−10 dB)in an entire UWB band(3.1–10.6)giga hertz(GHz).Moreover,the inter-element isolation has also been enhanced to>20 db for majority of the UWB *** antenna was fabricated and tested with the vector network analyzer(VNA)and in an anechoic chamber for scattering parameters and radiation ***,different MIMO diversity performance metrics are also measured to validate the proposed *** simulation results and the experimental results from the constructed model agree quite *** proposed antenna is compared with similar designs in recently published literature for various performance *** of its low envelope correlation coefficient(ECC<0.1),high diversity gain(DG>9.99 dB),peak gain of 4.6 dB,reduced channel capacity loss(CCL<0.4 b/s/Hz),and average radiation efficiency of over 85%,the proposed MIMO antenna is ideally suited for practical UWB applications.

关键词： Multiple input multiple output antennas envelope correlation coefficient defected ground structure ultra wide band diversity gain

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International Journal of Information and Communication technology 2024年第2期24卷 145-155页

作者： Wang, Kaiku Huang, Congkuan Yang, Yang Department of Computer Science and Technology Beijing University of Aeronautics and Astronautics Beijing100191 China Department of Electrical Engineering and Automation Hefei University of Technology Hefei230009 China

Aiming at the problem of low precision and large cleaning error in multi-link similar data mining, a multi-link similar data mining cleaning method based on Bayesian algorithm is proposed in this paper. On the basis of extracting multi-link data, the data is preprocessed and the similarity between the data is calculated. The data with high similarity is input into the Bayesian network, and the data cleaning process is completed according to the maximum likelihood value of the data. Experimental results show that the mining accuracy of the proposed method for similar data can reach 98.51%, and the cleaning error is about 1.22%, indicating that the proposed method can more effectively complete the mining and cleaning of similar data in multi-links. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Directed graphs

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TCIP: Transformed Colour Intensity Profiles analysis for fault detection in power line insulators

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Multimedia Tools and Applications 2025年第8期84卷 4503-4534页

作者： Tomaszewski, Michal Gasz, Rafal Kasana, Singara Singh Osuchowski, Jakub Singh, Simranjit Zator, Slawomir Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Department of Computer Science and Information Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Information Technology Dr B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Department of Safety Engineering and Technical Systems Faculty of Production Engineering and Logistics Opole University of Technology Prószkowska 76 Opole45-758 Poland

In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative need for a robust method to detect damage in power insulator disc images, introducing a novel feature extraction technique grounded in color intensity profile transformation and ensemble learning. For the purposes of the research, a specific dataset was developed based on publicly available images of power insulators. The collection consists of 9232 images of insulator discs which included 2184 images of damaged discs. The discernible damages include breakages and burnouts. Two distinct analysis variants were employed. In the first variant (V1), two classification groups were selected: disc with damages and disc without damages. In the second variant (V2), three classification groups were selected: discs without damage, broken discs, and burnout discs. The described research was divided into two successive stages. In the first of them (S1), the transformed color intensity profiles for the prepared data set were built and various machine learning models for their classification were trained and evaluated. In the next stage (S2), previously developed, highest efficient machine learning models, were used to make the detection of various damaged types of overhead line insulator discs. For the first stage of research high-performance results and a high value of the F1 score parameters were obtained (F1 score = 0.999 for the first variant (S1V1) and F1 score = 0.992 for the second variant (S1V2). In the second stage of research and the first variant (S2V1), the highest result of the F1 score was 0.932 and for the second variant (S2V2) F1 score was 0.930. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

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Number Plate Recognition Using OpenCV 6

Number Plate Recognition Using OpenCV

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

作者： Roopa Chandrika, R. Vanitha, K. Thahaseen, Aafiya Chandramma, R. Neerugatti, Vikram Mahesh, T.R. Faculty of Engineering Department of Computer Science and Engineering Coimbatore India Al-Ameen Engineering College Department of Computer Science and Engineering Erode India Bangalore India Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350306613

The advancement of automated number plate recognition (ANPR) systems has garnered noteworthy attention in recent times owing to their diverse applications across multiple domains, including traffic management, parking management, and law enforcement. This paper presents an innovative ANPR method using OpenCV, an open-source computer vision library. Developing ANPR systems is a great fit for OpenCV since it offers a flexible platform for image processing and computer vision tasks. The suggested method effectively detects and recognizes number plates from images and video streams by utilizing OpenCV's capabilities for feature extraction, image preprocessing, and machine learning. Character segmentation, optical character recognitlon (OCR), and licence plate localization are important stages in the process. The ANPR system's accuracy and effectiveness are increased by using these strategies. A variety of real-world datasets, including different lighting conditions, camera angles, and vehicle types, are used in extensive experiments to assess the system's performance. The outcomes show how well the OpenCV-based ANPR system performs in tasks requiring license plate recognition, attaining high accuracy and resilience. Additionally, covered in the paper are possible uses for the ANPR system in security systems, vehicle tracking, and traffic monitoring. To make sure the system is workable in a variety of situations, scalability and real-time implementation are also taken into account. © 2024 IEEE.

关键词： machine learning number plate OpenCV recognition

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Deep learning and vision transformers-based framework for breast cancer and subtype identification

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Neural Computing and Applications 2025年第16期37卷 9311-9330页

作者： Jahan, Ishrat Chowdhury, Muhammad E. H. Vranic, Semir Al Saady, Rafif Mahmood Kabir, Saidul Pranto, Zahid Hasan Mim, Sabiha Jahan Nobi, Sadia Farhana Department of Computer Science and Engineering Shahjalal University of Science and Technology Sylhet Bangladesh Department of Electrical Engineering Qatar University 2713 Doha Qatar College of Medicine QU Health Qatar University Doha Qatar Department of Electrical and Electronic Engineering University of Dhaka Dhaka1000 Bangladesh

Breast cancer, marked by uncontrolled cell growth in breast tissue, is the most common cancer among women and a second-leading cause of cancer-related deaths. Among its types, ductal and lobular carcinomas are the most prevalent, with invasive ductal carcinoma accounting for about 70–80% of cases and invasive lobular carcinoma for about 10–15%. Accurate identification is crucial for effective treatment but can be time-consuming and prone to interobserver variability. AI can rapidly analyze pathological images, providing precise, cost-effective identification, thus reducing the pathologists’ workload. This study utilizes a deep learning framework for advanced, automatic breast cancer detection and subtype identification. The framework comprises three key components: detecting cancerous patches, identifying cancer subtypes (ductal and lobular carcinoma), and predicting patient-level outcomes from whole slide images (WSI). The validation process includes visualization using Score-CAM to highlight cancer-affected areas prominently. Datasets include 111 WSIs (85 malignant from the Warwick HER2 dataset and 26 benign from pathologists). For subtype detection, there are 57 ductal and 8 lobular carcinoma cases. A total of 28,428 annotated patches were reviewed by two expert pathologists. Four pre-trained models—DenseNet-201, MobileNetV2, an ensemble of these two, and a Vision Transformer-based model—were fine-tuned and tested on the patches. Patient-level results were predicted using a majority voting technique based on the percentage of each patch type in the WSI. The Vision Transformer-based model outperformed other models in patch classification, achieving an accuracy of 96.74% for cancerous patch detection and 89.78% for cancer subtype classification. For WSI-based cancer classification, the majority voting method attained an F1-score of 99.06 and 96.13% for WSI-based cancer subtype classification. The proposed deep learning-based framework for advanced breast cancer det

关键词： Diseases

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Securing MIMO Wiretap Channel With Learning-Based Friendly Jamming Under Imperfect CSI

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IEEE Internet of Things Journal 2025年第11期12卷 16009-16022页

作者： Minh Tuan, Bui Nguyen, Diep N. Linh Trung, Nguyen Nguyen, Van-Dinh Van Huynh, Nguyen Thai Hoang, Dinh Krunz, Marwan Dutkiewicz, Eryk University of Technology Sydney School of Electrical and Data Engineering SydneyNSW2007 Australia University of Engineering and Technology Vietnam National University Faculty of Electronics and Telecommunications Hanoi100000 Viet Nam College of Engineering and Computer Science VinUniversity Hanoi100000 Viet Nam University of Liverpool Department of Electrical Engineering and Electronics LiverpoolL69 3GJ United Kingdom The University of Arizona Department of Electrical and Computer Engineering TucsonAZ85721 United States

Wireless communications are particularly vulnerable to eavesdropping attacks due to their broadcast nature. To effectively deal with eavesdroppers, existing security techniques usually require accurate channel state information (CSI), e.g., for friendly jamming (FJ), and/or additional computing resources at transceivers, e.g., cryptography-based solutions, which unfortunately may not be feasible in practice. This challenge is even more acute in low-end IoT devices. We thus introduce a novel deep learning-based FJ framework that can effectively defeat eavesdropping attacks with imperfect CSI and even without CSI of legitimate channels. In particular, we first develop an autoencoder-based communication architecture with FJ, namely, AEFJ, to jointly maximize the secrecy rate and minimize the block error rate (BLER) at the receiver without requiring perfect CSI of the legitimate channels. In addition, to deal with the case without CSI, we leverage the mutual information neural estimation (MINE) concept and design a MINE-based FJ scheme that can achieve comparable security performance to the conventional FJ methods that require perfect CSI. Extensive simulations in a multiple-input-multiple-output (MIMO) system demonstrate that our proposed solution can effectively deal with eavesdropping attacks in various settings. Moreover, the proposed framework can seamlessly integrate MIMO security and detection tasks into a unified end-to-end learning process. This integrated approach can significantly maximize the throughput and minimize the BLER, offering a good solution for enhancing communication security in wireless communication systems. © 2014 IEEE.

关键词： Jamming

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Resilient TCP Variant Enabling Smooth Network Updates for Software-Defined Data Center Networks

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Tsinghua science and technology 2024年第5期29卷 1615-1632页

作者： Abdul Basit Dogar Sami Ullah Yiran Zhang Hisham Alasmary Muhammad Waqas Sheng Chen Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China and also with Department of Informatics and SystemsUniversity of Management and TechnologyLahore 54660Pakistan Department of Computer Science Shaheed Benazir Bhutto UniversitySheringalUpper Dir 18050Pakistan School of Computer Science Beijing University of Posts and TelecommunicationsBeijing 100876China Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha 61421Saudi Arabia Department of Computer Engineering Faculty of Information TechnologyUniversity of BahrainSakheer 32038Bahrainand also with School of EngineeringEdith Cowan UniversityPerth WA 6027Australia School of Electronics and Computer Science University of SouthamptonSouthamptonSO171BJUK

Network updates have become increasingly prevalent since the broad adoption of software-defined networks(SDNs)in data *** TCP designs,including cutting-edge TCP variants DCTCP,CUBIC,and BBR,however,are not resilient to network updates that provoke flow *** this paper,we first demonstrate that popular TCP implementations perform inadequately in the presence of frequent and inconsistent network updates,because inconsistent and frequent network updates result in out-of-order packets and packet drops induced via transitory congestion and lead to serious performance *** look into the causes and propose a network update-friendly TCP(NUFTCP),which is an extension of the DCTCP variant,as a *** are used to assess the proposed *** findings reveal that NUFTCP can more effectively manage the problems of out-of-order packets and packet drops triggered in network updates,and it outperforms DCTCP considerably.

关键词： software defined data center networks network updates DCTCP out-of-order packets packet drop SDN

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A Comprehensive Evaluation Process by Analytical Hierarchical Process for Identification of Potential Groundwater Zones 2

A Comprehensive Evaluation Process by Analytical Hierarchica...

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2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Gudadhe, Amit Anil Reddy, K.T.V. Faculty of Engineering and Technology Computer Science and Design Department Wardha India Faculty of Engineering and Technology Wardha India

ISBN: (纸本)9798331528713

For social and economic development of any region, groundwater plays a very vital role. Surface water infiltration depends on various parameters of the earth. The parameters includes Slope, Geology, Soil Type, Land Use/Land Cover, Rainfall, Drainage Density based on the study area under consideration. There exists various techniques for recognizing of groundwater probable regions. This paper focuses specifically on the recognizing of the subsurface water probable regions by Analytical Hierarchy Process. The steps involved in the process are discussed in detailed and shows how the potential zone identification is based on value of weights evaluated. © 2024 IEEE.

关键词： Land use

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