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11th International Conference on Electrical, electronic and Computing engineering, IcETRAN 2024

作者： Grujev, Milan Ilic, Milos Milosavljevic, Aleksandar Ilic, Aleksandra Stoinev Faculty of Electronic engineering Dept. Computer Sciences Nis Serbia Toplica Academy of Applied Studies Dept. Computer Sciences Prokuplje Serbia

ISBN: (纸本)9798350386998

Tooth segmentation is a vital task in medical image analysis aimed at extracting and delineating tooth structures from computed tomography scans. This process plays a crucial role in various clinical applications, including dental diagnostics, treatment planning, and surgical interventions. Through the years, different segmentation approaches are applied on tooth scans that comes from different CT machines. Different approaches archive different segmentation results. In particular most of them provided promising results. The goal of this paper is to present current state of the art in this field. Our research mainly was focused on research results from last couple of years. In this way this paper represents good start for all researches which plan is to contribute in the field of tooth segmentation. © 2024 IEEE.

关键词： Image segmentation

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Application of Artificial Intelligence using Mammograms to Identify Breast Cancer 6

Application of Artificial Intelligence using Mammograms to I...

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6th International Conference on Computational Intelligence and Networks, CINE 2024

作者： Rath, Sudeshna Giri, Kalyanbrata Dash, Satya Ranjan Barra, Paola Abdullah, Azian Azamimi KIIT University School of Computer Engineering India University of Naples 'Parthenope' Department of Science and Technology Italy Universiti Malaysia Perlis Faculty of Electronic Engineering and Technology Malaysia

ISBN: (纸本)9798331516796

An affordable and precise way to identify breast cancer is through Mammography. It has significantly decreased mortality by detecting malignancies early and is essential for early detection. It has also increased survival rates. However, disparities in mammography access are still mostly driven by socioeconomic factors. Ongoing research aims to address these problems, improve screening methods, and raise the precision and usability of mammography. Additionally, radiologists are being assisted by computer-aided detection (CAD) and artificial intelligence (AI), which are being used to improve diagnostic accuracy. The goal of this research is to identify the best AI algorithms for breast cancer detection. We employ a range of preprocessing methods in this study, first resizing the images to see which method cleans up our data the best. After segmenting our images to locate the region of interest, we extract features using a local binary pattern. Numerous classification models have been employed, such as SVM, KNN, Random Forest, and Decision Tree. Moreover, CNN and RCN have been used for the same objective. Furthermore, it was shown that, generally speaking, neural networks outperformed classification. © 2024 IEEE.

关键词： Lung cancer

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Impact of Nanogap Thickness on Dielectric-Modulated Field-effect Transistor Biosensor Performance for Uncharged Biomolecules Detection

Impact of Nanogap Thickness on Dielectric-Modulated Field-ef...

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2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023

作者： Jasmi, M.S. Fathil, M.F.M. Arshad, M. K. Md Nuzaihan. M. N, M. Halim, N.H.A. Rahman, S.F.A. Ayoib, A. Shaifullah. A. S, M. Ibrahim, M.M. Universiti Malaysia Perlis Faculty of Electronic Engineering and Technology Arau Malaysia Universiti Malaysia Perlis Institute of Nano Electronic Engineering Kangar Malaysia Engineering Campus Universiti Sains Malaysia Nibong School of Electrical and Electronic Engineering Tebal Malaysia Universiti Malaysia Perlis Padang Faculty of Chemical Engineering & Technology Besar Malaysia Universiti Teknikal Malaysia Melaka Durian Faculty of Electronic and Computer Engineering Tunggal Malaysia

ISBN: (纸本)9798350333312

Uncharged biomolecules sensing performance of dielectric-modulated field-effect transistor (DMFET) biosensor at various nanogap thickness via semiconductor device simulation tool was assessed in this work. The device structures with 10 nm-, 15 nm-, and 20 nm-thick nanogap were constructed for this investigation. Each device structure was applied with dielectric constant ranging from 2 to 7 at the nanogap representing the presence of various biomolecules. These device structures were electrically simulated by supplying gate voltage from 0 V to 2 V and biased with drain voltage of 0.05 V for linear region of operation. Based on the extracted drain current, the reduction of nanogap thickness increase capacitance at the nanogap region. In additional, increase in nanogap's dielectric constant causing an increase of its capacitance, and translated into higher output drain current. Sensitivity calculation and analysis shows DMFET biosensor with 10 nm-thick nanogap demonstrated the highest sensitivity with 6.896 μA/dec, which possibly permit enhanced sensing of uncharged biomolecule. © 2023 IEEE.

关键词： Drain current

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Quaternion double random phase encoding for privacy-preserving cancelable biometrics

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Multimedia Tools and Applications 2024年第37期83卷 85065-85078页

作者： Nasr, Mahmoud Piórkowski, Adam Abd El-Samie, Fathi E. Department of Biocybernetics and Biomedical Engineering AGH University of Krakow Krakow Poland Faculty of Engineering and Technology Future University in Egypt Cairo Egypt Computer Vision Sano Centre for Computational Medicine Kraków Poland Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Manoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Biometrics has become a fundamental aspect in the constantly-changing field of security solutions. Nevertheless, the ongoing risk of hacking and the possibility of biometric data being compromised in security breaches emphasize the urgent need for inventive and reliable biometric authentication methods. Introducing cancelable biometrics is an advanced approach to enhance the security of biometric templates. Our research paper presents a unique variation of this approach that depends on the powerful Double Random Phase Encoding (DRPE) algorithm. By incorporating an auxiliary input biometric template and using quaternion mathematics, we get an exceptional level of performance that surpasses previous performance standards. The cancelable biometric recognition system we present demonstrates exceptional performance in simulation experiments, demonstrating its ability to remain robust even in the presence of noise. More precisely, the proposed cancelable face recognition system attains a notable area under the Receiver Operating Characteristic (ROC) curve of 0.994 and an exceptionally-low Equal Error Rate (EER) of 0.00174. The efficiency of our solution is amazing, with an average time of 0.056263 seconds for each generated secure template. This demonstrates both speed and efficacy in addressing current security concerns. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Biometrics

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Vision transformer with feature calibration and selective cross-attention for brain tumor classification

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Iran Journal of computer Science 2025年第2期8卷 335-347页

作者： Khaniki, Mohammad Ali Labbaf Mirzaeibonehkhater, Marzieh Manthouri, Mohammad Hasani, Elham Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Indiana University-Purdue University Indianapolis IN United States Faculty of Electrical and Electronic Engineering Shahed University Tehran Iran Department of Chemical and Environmental Engineering University of Cincinnati Cincinnati 45221 OH United States

Brain tumor classification is a challenging task in medical image analysis, with significant implications for patient diagnosis and treatment. The objective of this paper is to propose a novel approach to brain tumor classification using a Vision Transformer (ViT) with a novel cross-attention mechanism. Our approach leverages the strengths of transformers in modeling long-range dependencies and multi-scale feature fusion. We introduce two new mechanisms to improve the performance of the cross-attention fusion module: Feature Calibration Mechanism (FCM) and Selective Cross-Attention (SCA). The FCM calibrates the features from different branches to make them more compatible, while The SCA selectively attends to the most informative features. Our experimental results demonstrate that the proposed approach outperforms other state-of-the-art methods, including Convolutional Neural Networks (CNN), ViT, and Cross-attention ViT, achieving an accuracy of 98.93% and an F1-score of 98.83%. Furthermore, the addition of Stochastic Depth mechanism improves the accuracy to 99.24% and the F1-score to 99.23%. The proposed FCM and SCA mechanisms can be easily integrated into other ViT architectures, making them a promising direction for future research in medical image analysis. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Attention mechanism Brain tumor classification Deep learning Medical imaging analysis Vision transformer

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Real-Time Power Monitoring and Fault Detection in Power Distribution System Using FPGA and cRIO 9039

Real-Time Power Monitoring and Fault Detection in Power Dist...

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2024 International Conference on Innovations in Science, engineering and Technology, ICISET 2024

作者： Mithil, Md. Salman Khan Talha, Md. Abu Ahmad, Shameem Islam, Khandoker Mainul South Dakota School of Mines & Technology Department of Electrical Engineering and Computer Science Rapid CitySD57701 United States Faculty of Engineering Department of Electrical and Electronic Engineering Dhaka1229 Bangladesh

ISBN: (纸本)9798350355499

This paper details developing and implementing a comprehensive power monitoring system, designed for real-time data acquisition and fault detection. Utilizing a cRIO 9039 platform, the system measures voltage and current, calculates RMS values, frequency, and complex power, and identifies fault conditions in voltage levels, frequency, or power factor. A unique aspect of our approach integrates FPGA-based data processing, ensuring high-speed data handling and error detection without interrupting primary data flow. The system also features a user-friendly interface for real-time data display and fault management. If any errors have been detected, the user will be notified using visual and audio warning and the reading and timestamp corresponding to the fault will be recorded. The system accurately monitors power metrics and detects deviations, enhancing industrial power management systems. The architecture, workflow, and user interface design align with industrial standards, offering practical insights into power system monitoring. © 2024 IEEE.

关键词： Power distribution faults

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A Proposal for a New E-Waste Image Dataset Based on the UNU-KEYS Classification 23

A Proposal for a New E-Waste Image Dataset Based on the UNU-...

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23rd International Symposium on Electrical Apparatus and Technologies, SIELA 2024

作者： Iliev, Dimitar I. Marinov, Marin B. Ortmeier, Frank Technical University of Sofia Faculty of German Engineering and Industrial Management Sofia Bulgaria Technical University of Sofia Faculty of Electronic Engineering and Technologies Department of Electronics Sofia Bulgaria Otto-von-Guericke-University Magdeburg Faculty of Computer Science Software Engineering Magdeburg Germany

ISBN: (纸本)9798350382365

This paper introduces the largest and most diverse e-waste dataset to date, consisting of 19,613 pictures, 28,941 annotations, and 77 classes, where each class represents one visually distinctive type of electronic device. Furthermore, our dataset was structured using the United Nations University's UNU-KEYS classification, which ensures the compatibility of our dataset with the different e-waste classifications used worldwide and allowed us to choose more relevant dataset classes. The proposed methodology for image collection, annotation, and labeling is explained. The advantages and disadvantages of this dataset and how it can be improved in the future are presented. This dataset has been made open source with a permissive CC by 4.0 license so that it can be used to stimulate scientific progress in the field of automatic e-waste recognition, with the end goal of solving the global e-waste problem. The dataset is available online at https://***/electronic-waste-detection/e-waste-dataset-r0ojc. © 2024 IEEE.

关键词： dataset e-waste object detection UNU-KEYS WEEE

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A Method for Shape Retrieval of Flying Objects Using Satellite Communication Signals

A Method for Shape Retrieval of Flying Objects Using Satelli...

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2023 IEEE/CIC International Conference on Communications in China, ICCC Workshops 2023

作者： Li, Shuangyang Shen, Xi Huang, Defeng David Technical University of Berlin Faculty of Electrical Engineering and Computer Science Berlin Germany University of Western Australia Department of Electrical Electronic and Computer Engineering Perth Australia

ISBN: (纸本)9798350345407

The successful commercialization of satellite communication systems using low earth orbit (LEO) satellites has received significant attention. In this paper, we study the ability of shape retrieval for flying objects using LEO satellite signals. We first show that the object shape can be extracted from the received satellite signals via exploiting the diffraction pattern. Then, we derive a discrete system model that relates the shape of the flying object with the received signal at ground stations, where the impact of the satellite elevation angle is considered. We discuss the 'coherence time' for the considered shape retrieval problem and further propose a simple shape retrieval scheme using a linear filter to the combined received samples. Our numerical results verify the effectiveness of the proposed scheme, and demonstrate promising retrieval performance under various conditions. © 2023 IEEE.

关键词： Satellite communication systems

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Robust Device-Free Mmwave Sensing with Specular Reflection Interference Mitigation

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IEEE Transactions on Mobile Computing 2025年第7期24卷 5749-5764页

作者： Liu, Yulin Wang, Jie Gao, Qinghua Pan, Miao Fang, Yuguang Dalian Maritime University School of Information Science and Technology Dalian116026 China Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States City University of Hong Kong Department of Computer Science Hong Kong Hong Kong

Device-Free mmWave Sensing (DFWS) could sense target state by analyzing how target activities influence the surrounding mmWave signals. It has emerged as a promising sensing technology. However, when employing DFWS indoors, specular reflection interference arises due to the specular reflectors. This interference often induces ghost targets, impacting the accurate estimation of the number and position of targets, resulting in degradation in sensing performance. To tackle this issue, we delve into the generation mechanism of specular reflection interference and analyze its multi-domain characteristics. Through exploration, we discern its temporal sparsity, spatial symmetry or collinearity, and frequency correlation characteristics, and propose four metrics to measure them, accordingly. Specifically, we propose a temporal characteristic quantitative evaluation metric based on identity matching, spatial symmetry and collinearity quantitative evaluation metrics based on geometric analysis, and a frequency correlation quantitative evaluation metric based on Doppler velocity correction, respectively. Based on these metrics, we design a novel Specular Reflection Interference Mitigation (SRIM) method and develop a robust SRIM-DFWS prototype system based on a 60 GHz mmWave radar to validate our proposed method. Experimental results demonstrate that our proposed method could achieve accurate and effective mitigation of specular reflection interference in device-free target tracking. © 2002-2012 IEEE.

关键词： Radar interference

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Photonics Applications and Web engineering – WILGA 2024

Photonics Applications and Web Engineering – WILGA 2024

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Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2024

作者： Romaniuk, Ryszard S. Smolarz, Andrzej Wójcik, Waldemar Warsaw University of Technology Institute of Electronic Systems Poland Lublin University of Technology Faculty of Electrical Engineering and Computer Science Poland

ISBN: (数字)9781510685796

ISBN: (纸本)9781510685789

Wilga 2024 Summer Symposium on Photonics Applications and Web engineering was the 52th edition of the research and technical meetings series. Traditionally, the annual series of technical conferences and topical sessions lasted the whole week. They usually were split to one winter meeting in January and one or two summer events in May/June, and in September. The Covid epidemic and the war in Ukraine has changed a lot. The hybrid meetings were held in Wilga resort near Warsaw, owned by the Warsaw University of Technology. Now the meetings since 2022 were shifted to Lublin. Nearly 100 participants took part in all of the Wilga 2022 events, most of them being young researchers active in all aspects of photonics, electronics and ICT science and technology. Over 60 participants took part in Wilga 2024 meetings. Wilga Symposium embraces hardware and software technologies associated with photonics like optics, optical engineering, optoelectronics, electronics and electrical engineering, mechatronics, chemical and material engineering, applied physics, industrial solutions and applications. Around 50 papers were presented during Wilga 2024, oral and poster. Out of this number, some papers chosen by authors are published in this volume of Proc. SPIE mostly related to photonics. The major change was that during Wilga 2020, 2021, 2022 and 2024 Symposia, during summer editions, no traditional large young researcher sessions at large were possible to be organized. We hope that this will change and Wilga 2025 will return to a good tradition to organize concurrent social research sessions full of young researchers like was during Wilga 2019 and earlier. © 2024 SPIE.

关键词： Photonic devices

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