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Routing and Spectrum Allocation in Broadband Quantum Entanglement Distribution

IEEE Journal on Selected Areas in Communications 2025年第5期43卷 1856-1870页

作者： Bali, Rohan Tittelbaugh, Ashley N. Jenkins, Shelbi L. Agrawal, Anuj Horgan, Jerry Ruffini, Marco Kilper, Daniel C. Bash, Boulat A. The Department of Electrical and Computer Engineering Department University of Arizona TucsonAZ United States The School of Computer Science and Statistics CONNECT Center Trinity College Dublin Dublin Ireland The Electronic and Electrical Engineering Department CONNECT Centre Trinity College Dublin Dublin Ireland

We investigate resource allocation for quantum entanglement distribution over an optical network. We characterize and model a network architecture that employs a single broadband quasi-deterministic time-frequency heralded Einstein-Podolsky-Rosen (EPR) pair source, and develop a routing and spectrum allocation scheme for distributing entangled photon pairs over such a network. As our setting allows separately solving the routing and spectrum allocation problems, we first find an optimal polynomial-time routing algorithm. We then employ max-min fairness criterion for spectrum allocation, which presents an NP-hard problem. Thus, we focus on approximately-optimal schemes. We compare their performance by evaluating the max-min and median number of EPR-pair rates assigned by them, and the associated Jain index. We identify two polynomial-time approximation algorithms that perform well, or better than others under these metrics. We also investigate scalability by analyzing how the network size and connectivity affect performance using Watts-Strogatz random graphs. We find that a spectrum allocation approach that achieves higher minimum EPR-pair rate can perform significantly worse when the median EPR-pair rate, Jain index, and computational resources are considered. Additionally, we evaluate the effect of the source node placement on the performance. © 2025 IEEE. All rights reserved.

关键词： Polynomial approximation

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Deep Learning Based Side-Channel Attack Detection for Mobile Devices Security in 5G Networks

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1012-1026页

作者： Amjed A.Ahmed Mohammad Kamrul Hasan Ali Alqahtani Shayla Islam Bishwajeet Pandey Leila Rzayeva Huda Saleh Abbas Azana Hafizah Mohd Aman Nayef Alqahtani Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600Malaysia Imam Alkadhim University College Department of Computer Techniques EngineeringBaghdad 10066Iraq Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600Malaysia Department of Networks and Communications Engineering College of Computer Science and Information SystemsNajran UniversityNajran 61441Saudi Arabia Institute of Computer Science and Digital Innovation UCSI UniversityKuala Lumpur 56000Malaysia Department of Intelligent Systems and Cyber Security Astana IT UniversityAstana 20000Kazakstan Department of Computer Science College of Computer Science and EngineeringTaibah UniversityMadinah 42353Saudi Arabia Department of Electrical Engineering College of EngineeringKing Faisal UniversityAl-Hofuf 31982Saudi Arabia

Mobile devices within Fifth Generation(5G)networks,typically equipped with Android systems,serve as a bridge to connect digital gadgets such as global positioning system,mobile devices,and wireless routers,which are vital in facilitating end-user communication ***,the security of Android systems has been challenged by the sensitive data involved,leading to vulnerabilities in mobile devices used in 5G *** vulnerabilities expose mobile devices to cyber-attacks,primarily resulting from security ***-permission apps in Android can exploit these channels to access sensitive information,including user identities,login credentials,and geolocation *** such attack leverages"zero-permission"sensors like accelerometers and gyroscopes,enabling attackers to gather information about the smartphone's *** underscores the importance of fortifying mobile devices against potential future *** research focuses on a new recurrent neural network prediction model,which has proved highly effective for detecting side-channel attacks in mobile devices in 5G *** conducted state-of-the-art comparative studies to validate our experimental *** results demonstrate that even a small amount of training data can accurately recognize 37.5％of previously unseen user-typed ***,our tap detection mechanism achieves a 92％accuracy rate,a crucial factor for text *** findings have significant practical implications,as they reinforce mobile device security in 5G networks,enhancing user privacy,and data protection.

关键词： Fifth Generation(5G)networks smartphone information leakage Side-Channel Attack(SCA) deep learning

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Semi-Blind Channel Estimation and Achievable Rate Analysis for Uplink RIS-Enhanced Multi-User Networks

IEEE Open Journal of Vehicular Technology

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IEEE Open Journal of Vehicular Technology 2025年 6卷 1108-1139页

作者： Farghaly, Samar I. Ismail, Mohamed I. Fouda, Mostafa M. Alwakeel, Ahmed S. Tanta University Department of Electronics and Electrical Communications Engineering Faculty of Engineering Tanta31111 Egypt Idaho State University Department of Electrical and Computer Engineering College of Science and Engineering PocatelloID83209 United States Modern Academy for Engineering Department of Electronic Engineering and Communication Technology Cairo Governorate 4411602 Egypt Center for Advanced Energy Studies Idaho FallsID83401 United States Suez University Department of Electrical Engineering Faculty of Engineering Suez43221 Egypt

Future wireless networks could benefit from the energy-efficient, low-latency, and scalable deployments that Reconfigurable Intelligent Surfaces (RISs) offer. However, the creation of an effective low overhead channel estimate technique is a major obstacle in RIS-assisted systems, especially given the high number of RIS components and intrinsic hardware constraints. This research examines the uplink of a RIS-empowered multi-user MIMO communication system and presents a novel semi-blind channel estimate approach. Unlike current approaches, which rely on pilot-based channel estimation, our methodology uses data to estimate channels, considerably enhancing the achievable rate. We provide a closed-form deterministic expression for the uplink achievable rate in actual settings where the channel state information (CSI) must be estimated rather than assumed perfect. The results of the simulations show that the formula obtained is accurate, with a close alignment between the deterministic and actual achievable rates (generally between 2 5% deviations). The proposed approach outperforms traditional approaches, resulting in rate increases of up to 35–40%, especially in instances with more RIS elements. These findings illustrate RIS technology's tremendous potential to improve system capacity and coverage, providing useful insights for optimizing RIS adoption in future wireless networks. © 2020 IEEE.

关键词： Channel state information

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Fast Demodulation of OFDR-Based Distributed Sensing Based on Enhanced Buneman Frequency Estimation

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Journal of Lightwave Technology 2025年第9期43卷 4283-4289页

作者： Zhang, Zhaopeng Liu, Bo Liu, Xiao Li, Caiyun Alsalman, Osamah Zhu, Chen Zhejiang Laboratory Research Center for Novel Computing Sensing and Intelligent Processing Hangzhou311121 China King Saud University Department of Electrical Engineering College of Engineering Riyadh11421 Saudi Arabia Missouri University of Science and Technology Department of Electrical and Computer Engineering RollaMO65409 United States

Aiming at realizing high-efficiency distributed strain sensing through optical frequency domain reflectometry (OFDR), this paper introduces a fast demodulation algorithm to determine strain-induced spectral shifts from coarse Rayleigh backscattering (RBS) cross-correlation spectra. The proposed approach employs an enhanced Buneman frequency estimation (BFE) algorithm, enabling direct spectral shift analysis across coarse signals. By applying this algorithm, the need for dense interpolation in the conventional cross-correlation demodulation process—typically required for a finer spectral sampling interval but at the cost of demodulation efficiency—can be eliminated. Both theoretical analysis and experimental investigation reveal the equivalence of the BFE and conventional algorithms in terms of underlying physical principles and resultant demodulation noise distribution, establishing a strong foundation for adopting the BFE algorithm to improve demodulation efficiency without sacrificing performance metrics. Demonstration experiments using identical hardware configurations show that the proposed BFE method enhances demodulation efficiency by over 17 times without sacrificing other performance metrics, confirming its effectiveness and practicality. This advancement holds promise for improving the practical application of OFDR-based distributed sensing systems. © 1983-2012 IEEE.

关键词： Frequency domain analysis

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Impact of dissolution and precipitation on pore structure in CO2 sequestration within tight sandstone reservoirs

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Petroleum science 2025年第2期22卷 868-883页

作者： Hui Gao Kai-Qing Luo Chen Wang Teng Li Zhi-Lin Cheng Liang-Bin Dou Kai Zhao Nan Zhang Yue-Liang Liu School of Petroleum Engineering Xi'an Shiyou University Engineering Research Center of Development and Management for Low to Ultra-Low Permeability Oil & Gas Reservoirs in West China Ministry of Education Xi'an Key Laboratory of Tight Oil (shale Oil) Development Department of Electrical Engineering and Computer Science University of Stavanger School of Petroleum Engineering China University of Petroleum (Beijing)

Complex physical and chemical reactions during CO2sequestration alter the microscopic pore structure of geological formations,impacting sequestration *** investigate CO2sequestration dynamics,comprehensive physical simulation experiments were conducted under varied pressures,coupled with assessments of changes in mineral composition,ion concentrations,pore morphology,permeability,and sequestration capacity before and after ***,a method using NMR T2spectra changes to measure pore volume shift and estimate CO2sequestration is *** quantifies CO2needed for mineralization of soluble ***,when CO2dissolves in crude oil,the precipitation of asphaltene compounds impairs both seepage and storage ***,the impact of dissolution and precipitation is closely associated with storage pressure,with a particularly pronounced influence on smaller *** pressure levels rise,the magnitude of pore alterations progressively *** a pressure threshold of 25 MPa,the rate of change in small pores due to dissolution reaches a maximum of 39.14%,while precipitation results in a change rate of-58.05% for small *** observed formation of dissolution pores and micro-cracks during dissolution,coupled with asphaltene precipitation,provides crucial insights for establishing CO2sequestration parameters and optimizing strategies in low permeability reservoirs.

关键词： Dissolution Precipitation Pore structure CO 2 sequestration Unconventional reservoirs

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Advanced Helical Antenna Design for X-Band Applications Using AI

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Progress in Electromagnetics Research C 2025年 153卷 201-211页

作者： Zeain, Mohammed Yousif Abu, Maisarah Toding, Apriana Zakaria, Zahriladha Alsariera, Hussein Ullah, Ihsan Abdulbari, Ali Abdulateef Yon, Hamizan Taha, Bilal Salman Inam Abbasi, Muhammad Hang Tuah Jaya Melaka Durian Tunggal76100 Malaysia Makassar Indonesia Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan Information Technology Center University of Technology Baghdad Iraq Antenna Research Center College of Engineering School of Electrical Engineering Universiti Teknologi MARA Malaysia Department of Electrical and Electronics University Tenaga National Malaysia Malaysia

This paper presents the design, fabrication, and characterization of a novel 3D-printed helical antenna operating within the 9.4–10.8 GHz frequency band. The antenna, employing a lightweight paper substrate and a strip-based helical structure, exhibits robust circular polarization characteristics and wideband operation. Rigorous simulations predict a peak CP gain of 11.7 dBi at 9.8 GHz and a high simulated radiation efficiency of 95%. Experimental measurements validate these predictions, achieving a peak CP gain of 11.6 dBi at 9.8 GHz. This research demonstrates the potential of 3D-printed helical antennas for diverse applications in modern wireless communication systems, including 5G, satellite communication, and radar. Furthermore, this study leverages the power of Artificial Intelligence (AI) by employing the Grey Wolf Optimizer (GWO), a sophisticated metaheuristic algorithm, to optimize the antenna’s design. The GWO algorithm is utilized to efficiently search the design space and identify optimal values for key parameters, such as the number of turns, helix pitch, and helix diameter, with the objective of maximizing antenna gain to achieve a target of 15 dBi. This research highlights the potential of AI-driven optimization techniques in advancing the design of high-performance antennas for emerging wireless communication systems. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Helical antennas

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AtheroRisk: An Integrated computer Software System for Stroke Risk Stratification Utilizing Carotid Plaque Analysis in Ultrasound Videos

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SN computer science 2025年第2期6.0卷 1-16页

作者： Gemenaris, Michalis Liapi, Georgia D. Markides, Christos Constantinou, Kyriacos Loizou, Christos P. Neophytou, Michalis Kardoulas, Dimitrios Pattichis, Marios S. Griffin, Maura Nicolaides, Andrew Pattichis, Constantinos S. Kyriacou, Efthyvoulos Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Department of Computer Science and Engineering Frederick University Nicosia Cyprus Department of Computer Science University of Cyprus Nicosia Cyprus American Medical Center Nicosia Cyprus Vascular Surgery Clinic Attikon General University Hospital Athens Greece Department of Electrical and Comp. Engineering Univ. of New Mexico Albuquerque NM United States Vascular Screening and Diagnostic Center Nicosia Cyprus

In this study we propose and evaluate AtheroRisk, a standalone integrated computer software system for the analysis of carotid B-mode ultrasound (U/S) images and videos. Our goal was to provide a tool to help physicians stratify stroke risk. The presented system is based on outcomes from different research studies, as well as European guidelines for the evaluation and treatment of carotid artery disease. The goal is to enable reproducible analysis of atherosclerotic plaques in real time. AtheroRisk brings together analysis of U/S image and/or video of the carotid arteries facilitating anonymization, standardization, noise filtering and segmentation of plaques;followed by image and motion feature extraction to derive plaque-composition and stability. All the above steps are combined to determine the annual stroke risk rate and the 5-year stroke-free survival rate. The system is powered by an SQLite local database, in which the end user can save and manage data extracted from processing and analysis in an anonymized way. The first version of AtheroRisk was developed following an incremental software development process. The developed system was verified using 54 U/S videos (27 Asymptomatic, AS;27 Symptomatic, SY cases) while the clinician’s satisfaction and comments were collected through a questionnaire-based validation process. The results show that the integrated system proposed in this study can be successfully used for the automated image and video analysis of the CCA plaque in ultrasound videos. © The Author(s) 2025.

关键词： Carotid plaque analysis Motion analysis Plaque features Stroke risk stratification Ultrasound video

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Advancements in Liver Tumor Detection:A Comprehensive Review of Various Deep Learning Models

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computer Modeling in engineering & sciences 2025年第1期142卷 91-122页

作者： Shanmugasundaram Hariharan D.Anandan Murugaperumal Krishnamoorthy Vinay Kukreja Nitin Goyal Shih-Yu Chen Deptartment of Artificial Intelligence and Data Science Vardhaman College of EngineeringHyderabad501218India Deptartment of CSE V.S.B College of EngineeringKarur639111India Deptartment of Electrical and Electronics Engineering Vardhaman College of EngineeringHyderabad501218India Centre for Research Impact&Outcome Chitkara UniversityRajpura140401PunjabIndia Department of Computer Science and Engineering School of Engineering and TechnologyCentral University of HaryanaMahendergarh123031HaryanaIndia Department of Computer Science and Information Engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan Intelligence Recognition Industry Service Research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan

Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment *** Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and *** review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and *** metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical *** review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging *** suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular *** paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.

关键词： Liver tumor detection liver tumor segmentation image processing liver tumor diagnosis feature extraction tumor classification deep learning machine learning

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Energy-Efficient Fast Object Detection on Edge Devices for IoT Systems

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IEEE Internet of Things Journal 2025年第11期12卷 16681-16694页

作者： Achmadiah, Mas Nurul Ahamad, Afaroj Sun, Chi-Chia Kuo, Wen-Kai National Formosa University SMIM Research Center the Department of Electro-Optics Yunlin Taiwan Yuan Ze University Department of Computer Science and Engineering Taoyuan Taiwan National Taipei University Department of Electrical Engineering Taipei Taiwan National Formosa University Department of Electro-Optics Yunlin Taiwan

This paper presents an Internet of Things (IoT) application that utilizes an AI classifier for fast-object detection using the frame difference method. This method, with its shorter duration, is the most efficient and suitable for fast-object detection in IoT systems, which require energy-efficient applications compared to end-to-end methods. We have implemented this technique on three edge devices: AMD AlveoTMU50, Jetson Orin Nano, and Hailo-8TMAI Accelerator, and four models with artificial neural networks and transformer models. We examined various classes, including birds, cars, trains, and airplanes. Using the frame difference method, the MobileNet model consistently has high accuracy, low latency, and is highly energy-efficient. YOLOX consistently shows the lowest accuracy, lowest latency, and lowest efficiency. The experimental results show that the proposed algorithm has improved the average accuracy gain by 28.314%, the average efficiency gain by 3.6 times, and the average latency reduction by 39.305% compared to the end-to-end method. Of all these classes, the faster objects are trains and airplanes. Experiments show that the accuracy percentage for trains and airplanes is lower than other categories. So, in tasks that require fast detection and accurate results, end-to-end methods can be a disaster because they cannot handle fast object detection. To improve computational efficiency, we designed our proposed method as a lightweight detection algorithm. It is well suited for applications in IoT systems, especially those that require fast-moving object detection and higher accuracy. © 2025 IEEE.

关键词： Neural networks

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Novel Computational Photography for Soft-Focus Effect in Automatic Post Production

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IEEE Transactions on Image Processing 2025年 34卷 2560-2574页

作者： Tsai, Hao-Yu Tsai, Morris C.-H Huang, Scott C.-H Wu, Hsiao-Chun National Tsing Hua University Department of Electrical Engineering Hsinchu300044 Taiwan Louisiana State University School of Electrical Engineering and Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center for AI Applications Chungli Taoyuan City320315 Taiwan

The well-known soft-focus effect, which relies on either special optical filters or manual post-production techniques, has been intriguing and powerful in photography for quite a while. Nonetheless, how to impose the soft-focus effect automatically simply using sophisticated image-processing (computational photography) algorithms has never been addressed in the literature to the best of our knowledge. In this work, we would like to make the first-ever attempt to design an automatic, optical-filter-free approach to create the appropriate soft-focus effects desired by individual users. Our approach is first to investigate the physical optical filter, namely Kenko Black Mist No. 5, and estimate the corresponding kernel matrix (i.e., the system impulse response matrix) using our proposed novel irradiance-domain kernel-matrix estimation framework. Furthermore, we demonstrate that it is not feasible to find a kernel matrix that precisely characterizes the soft-focus effect by just using a pixel-value-domain image (a regular photo) in post production. To combat the aforementioned problem, we establish a novel pixel-value-to-pseudo-irradiance map such that the pseudo irradiance-domain image can be obtained directly from any pixel-value-domain image. Finally the soft-focus effect can be created from the two-dimensional convolution between the pseudo irradiance-domain image and the estimated kernel. To evaluate our proposed automatic scheme for soft-focus effect, we compare the results from our proposed new scheme and the physical optical filter in terms of the DCT-KLD (Kullback-Leibler divergence of discrete cosine transform) and the conventional PSNR (peak-signal-to-noise ratio). Experiments show that our proposed new scheme can achieve very small DCT-KLDs and very large PSNRs over the ground truth, namely the results from the physical optical filter. © 1992-2012 IEEE.

关键词： Tomography

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