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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

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

ISBN: (纸本)9798350368741

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 l1-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. © 2025 IEEE.

关键词： cross array near-field source localization spatial-temporal underdetermine estimation

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How to Approach Security Testing of Web 3.0 Solutions: A Review of Existing Knowledge 11

How to Approach Security Testing of Web 3.0 Solutions: A Rev...

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11th Workshop on Software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2024

作者： Jeršič, Nika Turkanović, Muhamed Beranič, Tina University of Maribor The Faculty of Electrical Engineering and Computer Science Koroška cesta 46 Maribor2000 Slovenia

Despite its promising advancements, Web 3.0 solutions still encounter significant challenges, particularly in the realm of software testing and security testing. This paper introduces a literature review of existing research in the fields of Web 3.0 technologies and security testing. We found there is little research on the connection between these fields. Most security research in Web 3.0 is focused on smart contracts and network attacks, like Denial-of-Service (DoS). Our analysis identifies significant trends, attacks and mitigations in overlapping topics within the current body of research. Understanding these challenges is crucial for ensuring the reliability and security of Web 3.0 solutions as they become more integrated into mainstream technology. © 2024 Copyright for this paper by its authors.

关键词： Blockchain Quality assurance Security testing Smart contracts Web 3.0

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Progressive Education: Augmented Reality Visualization of Human Anatomy on HoloLens 2 8

Progressive Education: Augmented Reality Visualization of Hu...

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8th Human-computer Interaction Slovenia Conference, HCI SI 2023

作者： Shishkov, Aleksandr Kolmanič, Simon University of Maribor Faculty of Electrical Engineering and Computer Science Koroška cesta 46 Maribor2000 Slovenia

The landscape of medical education is undergoing a transformative shift driven by rapid technological evolution. In the 21st century, innovative platforms, notably Augmented Reality (AR), play a crucial role in creating immersive and interactive learning environments, especially in medicine. The HoloLens headset, representing a leading AR platform, stands out in revolutionizing medical education by seamlessly merging the physical and digital realms. This article explores the development of an AR application for HoloLens 2, specifically focusing on visualizing human anatomy and highlighting intricate details of implants within the human system. The primary objective is to enrich the learning experience, providing a comprehensive understanding of anatomical structures through the lens of cutting-edge technology. © 2024 Copyright for this paper by its authors.

关键词： Augmented reality Human anatomy Microsoft HoloLens 2

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Power System Dynamic Properties after Implementation of PSS and Inertia Decrease

Power System Dynamic Properties after Implementation of PSS ...

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Kljajić, Ružica Marić, Predrag Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering Computer Science and Information Technology Osijek Croatia

ISBN: (纸本)9789531842976

Low inertia of the power system combined with low damping impairs the power system's ability to cope with disturbances that can significantly affect system stability. In such a case, in addition to speed or frequency deviations of the generator, low-frequency oscillations also occur and suitable ways must be found to mitigate them. In this paper, an oscillatory stability as well as the time domain generator's speed deviations were observed in an IEEE 14-bus system in four simulation scenarios after improving the system damping by implementing a Power System Stabilizer (PSS) and the system inertia was changed by integrating wind farm with fully rated converter interfaced wind generators. © 2024 IEEE.

关键词： Damping

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Exploring the Usage of Mobile Phones in the Assessment Process: A Case Study 47

Exploring the Usage of Mobile Phones in the Assessment Proce...

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47th ICT and Electronics Convention, MIPRO 2024

作者： Kovačević, Željko Bubnic, Bostjan Kosar, Tomaž Zagreb University Of Applied Sciences Department Of Computer Science And Information Technology Zagreb Croatia University Of Maribor Faculty Of Electrical Engineering And Computer Science Maribor Slovenia

ISBN: (纸本)9798350382495

Technology is changing how students learn in the 21st century significantly. Integrating mobile devices in teaching, learning, and assessment processes has emerged as an important strategy for improving teaching methodologies and students' learning. However, adopting mobile devices presents several challenges, including understanding the students' performance, impact on time, and efficiency in the assessment process. This study explores this area with an empirical study of using mobile devices and compares the results to those using traditional desktop computers. In the educational environment, we investigated students' effective use while interacting with mobile and desktop versions of the Second Introductory programming summative assessment. Multinational/multi-institutional research involved a comparative analysis between two student groups undertaking identical tasks on mobile phones and desktop computers. Our results suggest that the students' results are not affected significantly by using the mobile version of the assessment application. These results highlight the usability of mobile devices as a flexible and effective tool for various educational applications, strengthening their role in the modern learning environment. © 2024 IEEE.

关键词： Object oriented programming

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Arabic Handwritten Document OCR Solution with Binarization and Adaptive Scale Fusion Detection 6

Arabic Handwritten Document OCR Solution with Binarization a...

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6th IEEE Novel Intelligent and Leading Emerging sciences Conference, NILES 2024

作者： Waly, Alhossien Tarek, Bassant Feteha, Ali Yehia, Rewan Amr, Gasser Fares, Ahmed Egypt-Japan University of Science and Technology E-JUST Faculty of Engineering Computer Science and Engineering Departement Alexandria21934 Egypt Benha University Faculty of Engineering Electrical Engineering Department Cairo11629 Egypt

ISBN: (纸本)9798350378511

The problem of converting images of text into plain text is a widely researched topic in both academia and industry. Arabic handwritten Text Recognation (AHTR) poses additional challenges due to diverse handwriting styles and limited labeled data. In this paper we present a complete OCR pipeline that starts with line segmentation using Differentiable Binarization and Adaptive Scale Fusion techniques to ensure accurate detection of text lines. Following segmentation, a CNN-BiLSTM-CTC architecture is applied to recognize characters. Our system, trained on the Arabic Multi-Fonts Dataset (AMFDS), achieves a Character Recognition Rate (CRR) of 99.20% and a Word Recognition Rate (WRR) of 93.75% on single-word samples containing 7 to 10 characters, along with a CRR of 83.76% for sentences. These results demonstrate the system's strong performance in handling Arabic scripts, establishing a new benchmark for AHTR systems. © 2024 IEEE.

关键词： Arabic Optical Character Recognition convolutional neural networks line segmentation recurrent neural networks Scene text detection

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Incident Detection with Pruned Residual Multilayer Perceptron Networks 18

Incident Detection with Pruned Residual Multilayer Perceptro...

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18th Conference on computer science and Intelligence Systems, FedCSIS 2023

作者： Soubra, Mohamad Dorohinicki, Marek-Kisiel Kurdziel, Marcin Zachara, Marek Agh University Faculty of Computer Science Electronics and Telecommunications Krakow Poland Agh University Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Krakow Poland

ISBN: (纸本)9788396744784

Internet of things (IoT) has opened new horizons in connecting all sorts of devices to the internet. However, continuous demand for connectivity increases the cybersecurity risks, rendering IoT devices more prone to cyberattacks. At the same time, rapid advances in Deep Learning (DL)-based algorithms provide state-of-the-art results in many classification tasks, including classification of network traffic or system logs. That said, deep learning algorithms are considered computationally expensive as they require substantial processing and storage capacity. Sadly, IoT devices have limited resources, making renowned DL models hard to implement in this environment. In this paper we present a Residual Neural Network inspired DL-based Intrusion Detection System (IDS) that incorporates weight pruning to make the model more compact in size and resource consumption. Additionally, the proposed system leverages feature selection algorithms to reduce the feature-space size. The model was trained on the NSL-KDD dataset benchmark. Experimental results show that the proposed system is effective, being able to classify network traffic with an F1 score of up to 98.9% before the pruning and an F1 score of up to 97.5% after pruning 90% of network weights. © 2023 Polish Information Processing Society.

关键词： Internet of things

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Analyzing Data Characteristics for Learning OPFs

Analyzing Data Characteristics for Learning OPFs

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Lugmania, Hugo Luna, Jocellyn Rodriguez-Veliz, Xavier Cordova-Garcia, Jose Escuela Superior Politécnica Del Litoral Espol Faculty of Electrical Engineering and Computer Science Guayaquil Ecuador

ISBN: (纸本)9789531842976

Renewable energy sources have altered the generation and loading characteristics of modern electrical power systems, which is why finding the solution to the Power Flow Problem (OPF) has increased in complexity and the need to solve it more frequently. Despite increasing complexity, the OPF has a known structure presenting features that allow the use of Machine Learning (ML) to find solutions. This paper sets out to investigate the effects of varying specific characteristics of the input data used to train ML models for solving the OPF problem, particularly the load. We examine how the sample size, load correlation coefficient and maximum load deviation impact the performance of a neural network trained to predict OPF solutions. The results of this research demonstrate a clear correlation between these variations in the training dataset and the performance of different ML models. © 2024 IEEE.

关键词： Feasibility metrics Machine Learning Neural Networks OPF Training Data Variability

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Fuzzy clustering for electric field characterization and its application to thunderstorm interpretability

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Digital Communications and Networks 2025年第2期11卷 299-307页

作者： Xu Yang Hongyan Xing Xinyuan Ji Wei Xu Witold Pedrycz School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Department of Electrical and Computer Engineering University of AlbertaEdmonton AB T6G 2R3Canada Systems Research Institute Polish Academy of Sciences00-901 WarsawPoland Department of Computer Engineering Faculty of Engineering and Natural SciencesIstinye University34010 IstanbulTurkey

Changes in the Atmospheric Electric Field Signal(AEFS)are highly correlated with weather changes,especially with thunderstorm ***,little attention has been paid to the ambiguous weather information implicit in AEFS *** this paper,a Fuzzy C-Means(FCM)clustering method is used for the first time to develop an innovative approach to characterize the weather attributes carried by ***,a time series dataset is created in the time domain using AEFS *** AEFS-based weather is evaluated according to the time-series Membership Degree(MD)changes obtained by inputting this dataset into the ***,thunderstorm intensities are reflected by the change in distance from a thunderstorm cloud point charge to an AEF ***,a matching relationship is established between the normalized distance and the thunderstorm dominant MD in the space ***,the rationality and reliability of the proposed method are verified by combining radar charts and expert *** results confirm that this method accurately characterizes the weather attributes and changes in the AEFS,and a negative distance-MD correlation is obtained for the first *** detection of thunderstorm activity by AEF from the perspective of fuzzy set technology provides a meaningful guidance for interpretable thunderstorms.

关键词： Atmospheric electric field(AEF) Thunderstorm Fuzzy C-means(FCM) Attribute

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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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