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CMTJ:Simulation package for analysis of multilayer spintronic devices

npj Computational Materials 2023年第1期9卷 1804-1813页

作者： Jakub Mojsiejuk Sławomir Ziętek Krzysztof Grochot Witold Skowroński Tomasz Stobiecki Institute of Electronics AGH University of Science and TechnologyAl.Mickiewicza 30Kraków 30-059Poland Faculty of Physics and Applied Computer Science AGH University of Science and TechnologyAl.Mickiewicza 30Kraków 30-059Poland

We present CMTJ—a simulation package for large-scale macrospin analysis of multilayer spintronics *** from conventional simulations,such as magnetoresistance and magnetisation hysteresis loops,CMTJ implements a mathematical model of dynamic experimental techniques commonly used for spintronics devices characterisation,for instance:spin diode ferromagnetic resonance,pulse-induced microwave magnetometry,or harmonic Hall voltage *** find that macrospin simulations offer a satisfactory level of agreement,demonstrated by a variety of *** a unified simulation package,CMTJ aims to accelerate wide-range parameter search in the process of optimising spintronics devices.

关键词： multilayer analysis hysteresis

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Efficient Saliency Map Detection for Low-Light Images Based on Image Gradient

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IEEE Transactions on Circuits and Systems for Video technology 2024年第2期34卷 852-865页

作者： Lin, Chun-Yi Haq, Muhamad Amirul Chen, Jiun-Han Ruan, Shanq-Jang Naroska, Edwin National Taiwan University of Science and Technology Department of Electronic and Computer Engineering Taipei10607 Taiwan Hochschule Niederrhein University of Applied Science Faculty of Electrical Engineering and Computer Science Krefeld47805 Germany

Recently, deep learning has been widely employed across various domains. The Convolution Neural Network (CNN), a popular deep learning algorithm, has been successfully utilized in object recognition tasks, such as face recognition, vehicle recognition, and license plate recognition. However, conventional methods for object recognition may not be appropriate for low-light image recognition due to information loss in the dark regions and unexpected noise that can impair object quality. Therefore, the development of specialized techniques for low-light image enhancement has become a major research focus for object detection. This paper proposed a gradient-based saliency map detection method with an improved ResNet architecture that outperforms previous works in detecting multiple or large objects. Additionally, the proposed method enhances images with the object as the center and emphasizes foreground-background differences. Compared with previous works, this paper achieves1.28× improvements in the parameters and 1.32× faster inference speed than the original ResNet architecture. © 1991-2012 IEEE.

关键词： Neural networks

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Throughput Prediction Using LS-SVM For 4g-LTE Network and Beyond

Throughput Prediction Using LS-SVM For 4g-LTE Network and Be...

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2024 International Conference on Telecommunications and Intelligent Systems, ICTIS 2024

作者： Hamdani, Mostefa Sahnoune, Ahmed Merzougui, Mokhtar Douara, Abdelmalek Khatemi, Fouad University El Wancharissi Laboratory of Electronics Computer Science and Applied Mathematics Faculty of Science and Technology Department of Mathematics and Computer Science Algeria University El Wancharissi Laboratory of Electronics Computer Science and Applied Mathematics Faculty of Science and Technology Department of Science and Technology Algeria

ISBN: (纸本)9798331527396

The integration of Artificial Intelligence(AI) with Long-Term Evolution (LTE) networks offers substantial potential for improving communication infrastructure. By harnessing AI algorithms, it is possible to dynamically optimize network parameters, proactively predict and mitigate equipment failures, and enhance Quality of Service (QoS) by prioritizing critical services through real-time analysis of key performance indicators. This study focuses on predicting network throughput using Least Square Support Vector Machine (LS-SVM). The predictive models developed can trigger adaptive network reconfigurations, ensuring that the network responds promptly to changing conditions. Simulation results reveal that the integration of LS-SVM significantly improves prediction accuracy, enabling more effective implementation of self-organizing network strategies in real-time. © 2024 IEEE.

关键词： Long Term Evolution (LTE)

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The study of copper oxide nanoparticles based on the pH varying during propolis-mediated synthesis: structure, optical properties, UV-block ability, and malachite green photodegradation

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applied Nanoscience (Switzerland) 2024年第3期14卷 585-602页

作者： Murshed, Mohammad N. Galil, Mansour S. Abdul Mohammed, Samir Osman El Sayed, Mohamed E. Al‑qubati, Mohyeddine Saif, Ebkar Abdo Ahmed Physics Department Faculty of Science and Arts King Khalid University Muhayl Asser Abha Saudi Arabia Chemistry Department Faculty of Applied Science Taiz University Taiz Yemen Faculty of Engineering Al-Janad University for Science and Technology Taiz Yemen Physics Department Faculty of Science Ibb University Ibb Yemen Physics Department Faculty of Applied Science Taiz University Taiz Yemen Faculty of Medical Al-Janad University for Science and Technology Taiz Yemen

In third-world countries, the biosynthesis of multi-purpose copper oxide nanoparticles is a crucial solution for pollution, but studies on controlling their properties through internal structure are still limited. This work generated copper oxide nanoparticles (CONPs) using bee propolis as a reducing and capping agent, employing an ecologically benign, simple, inexpensive, and economical technique. The pH of this biosynthesis was varied (6.4, 7.8, 9.2, 10.4, and 11.7). The study computed various structural and optical parameters of biosynthesized CONP samples, revealing nonlinear changes with pH, including unit cell, Cu–O bond length, crystal size, microstrain, energy band gap, Urbach energy, and more. The current research has shown promising results in blocking ultraviolet rays effectively. The blocking parameters were calculated for CONPs samples, and it was found that the pH 8 sample had the best blocking capacity at both regions A and B (90.31 and 91.31%, respectively). The study effectively investigated CONPs’ potential as a catalyst for increasing dye photodegradation. The pH 6.4 sample showed the highest degradation rate (94.15%). The UV-blocking and photodegradation properties of the CONPs samples were explained using the structural and optical parameters. © King Abdulaziz City for science and technology 2024.

关键词： Energy gap

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An Innovative Approach Using TKN-Cryptology for Identifying the Replay Assault

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computers, Materials & Continua 2024年第1期78卷 589-616页

作者： Syeda Wajiha Zahra Muhammad Nadeem Ali Arshad Saman Riaz Muhammad Abu Bakr Ashit Kumar Dutta Zaid Alzaid Badr Almutairi Sultan Almotairi Department of Computer Science Alhamd Islamic UniversityIslamabad44000Pakistan Department of Computer Science and Technology University of Science and Technology BeijingBeijing100083China Department of Computer Science National University of TechnologyIslamabad44000Pakistan Department of Electrical Engineering National University of TechnologyIslamabad44000Pakistan Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of Computer Science Faculty of Computer and Information SystemsIslamic University of MadinahMedinah42351Saudi Arabia Department of Information Technology College of Computer Sciences and Information Technology CollegeMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Natural and Applied Sciences Faculty of Community CollegeMajmaah UniversityMajmaah11952Saudi Arabia

Various organizations store data online rather than on physical *** the number of user’s data stored in cloud servers increases,the attack rate to access data from cloud servers also *** researchers worked on different algorithms to protect cloud data from replay *** of the papers used a technique that simultaneously detects a full-message and partial-message replay *** study presents the development of a TKN(Text,Key and Name)cryptographic algorithm aimed at protecting data from replay *** program employs distinct ways to encrypt plain text[P],a user-defined Key[K],and a Secret Code[N].The novelty of the TKN cryptographic algorithm is that the bit value of each text is linked to another value with the help of the proposed algorithm,and the length of the cipher text obtained is twice the length of the original *** the scenario that an attacker executes a replay attack on the cloud server,engages in cryptanalysis,or manipulates any data,it will result in automated modification of all associated values inside the *** mechanism has the benefit of enhancing the detectability of replay ***,the attacker cannot access data not included in any of the papers,regardless of how effective the attack strategy *** the end of paper,the proposed algorithm’s novelty will be compared with different algorithms,and it will be discussed how far the proposed algorithm is better than all other algorithms.

关键词： Replay attack malware message attack file encryption cryptology data security

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A DES Homomorphic Scheme for Blackbox Data Analytics 4

A DES Homomorphic Scheme for Blackbox Data Analytics

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4th International Multidisciplinary Information technology and Engineering Conference, IMITEC 2024

作者： Mletshe, Luthando Modiba, Nthabiseng Makhoere, Lucky Ntlatywa, Phumezo Nogwina, Mnoneleli Chibaya, Colin Computer Science and Information Technology Faculty of Natural and Applied Science Kimberley South Africa

ISBN: (纸本)9798350387988

Data confidentiality is a critical concern in corporate settings, particularly as data analysts seek to uncover trends and insights from sensitive datasets. Traditional approaches often require plaintext data, posing a significant risk to data privacy during analytics processes. In response to this challenge, homomorphic encryption schemes have emerged as a promising solution to enable secure data analytics while preserving confidentiality. In this work-in-progress paper, we present an ongoing implementation of a homomorphic scheme based on the Data Encryption Standard (DES) as a proof of concept. Our goal is to showcase how DES homomorphic encryption can facilitate secure data analytics by allowing computations on encrypted data without compromising confidentiality. While our work is still in the early stages, we aim to empower data custodians by enabling them to share complete cipher datasets with confidence, knowing that data analytics operations remain blackbox and preserve data availability. Overall, this work represents an ongoing effort to advance data security practices and contribute to the development of practical solutions for secure data analytics. © 2024 IEEE.

关键词： Data Analytics

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NGC 4117:A New Compton-thick AGN Revealed by Broadband X-Ray Spectral Analysis

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Research in Astronomy and Astrophysics 2023年第5期23卷 19-26页

作者： Pavithra Mohanadas Adlyka Annuar Department of Applied Physics Faculty of Science and TechnologyUniversiti Kebangsaan Malaysia43600 UKM BangiSelangorMalaysia

In this paper,we present the broadband(0.5–195 keV)X-ray spectral analysis for one of the newly detected AGNs in the Swift-BAT 105 month Hard X-ray Survey Catalog,NGC *** to our ongoing research on low luminosity AGNs from the Swift-BAT 105 month catalog,we examine whether they are indeed low luminosity or heavily obscured *** of the AGNs in our sample is NGC 4117,where we discover it could be potentially a *** to examine NGC 4117 in detail,we combined the high energy Swift-BAT data with low energy data from XMM-Newton and Swift-XRT,and fitted the spectra simultaneously using physically-motivated models.A high absorption occurred at lower energies,i.e.,below 3 *** studies suggested that NGC 4117was heavily obscured with a large column density(~10^(23)cm^(-2)).Our fitting suggests that this AGN is in the Compton-thick regime with a predicted line-of-sight column density(N_(H,los))of 3.82×1024cm^(-2)and a torus column density(N_(H,tor))of 3.07×10^(24)cm^(-2).Both models yield intrinsic luminosity of 1.03×10^(42)erg s^(-1)at 2–10 keV while our bolometric luminosity is 2.05×10^(43)erg s^(-1),indicating that NGC 4117 is not an intrinsically low luminosity ***,it is a standard *** value of Eddington ratio that we obtained is 0.22,suggesting a very high accretion rate for this AGN.

关键词： galaxies active-X-rays galaxies-techniques spectroscopic

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EFFICIENT MODELING OF POLARIZED REFLECTION SPECTRA IN METASURFACES USING DEEP LEARNING FRAMEWORKS

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UPB Scientific Bulletin, Series A: applied Mathematics and physics 2025年第1期87卷 189-198页

作者： Ilie, Alexandra Mănăilă-Maximean, Doina Dănilă, Octavian Faculty of Engineering in Foreign Languages National University of Science and Technology POLITEHNICA of Bucharest Romania Dept. of Physics National University of Science and Technology POLITEHNICA of Bucharest Romania Academy of Romanian Scientists Romania Faculty of Applied Sciences National University of Science and Technology POLITEHNICA of Bucharest Romania

Modeling the electromagnetic responses of metasurfaces, advanced materials engineered to manipulate electromagnetic waves, remains computationally intensive, particularly for complex geometries such as polygonal and ringlike designs. This study explores the potential of frequency-domain prediction, followed by spectral transformation, as a viable approach for capturing x-and y-polarized reflection spectra of metasurfaces. To this end, a deep learning framework is developed, combining Variational Autoencoders (VAEs) and Convolutional Neural Networks (CNNs). The VAE effectively encodes spectral features in a low-dimensional latent space, while the CNN utilizes residual connections to directly map metasurface patterns to their spectral responses. By integrating frequency-domain representations with inverse Fourier transforms, the framework ensures compatibility with traditional time-domain data while maintaining computational efficiency. The proposed models achieve high predictive accuracy, with the VAE outperforming the CNN across multiple error metrics. This dual focus on methodological development and performance evaluation demonstrates the feasibility and advantages of integrating machine learning for rapid and precise metasurface analysis and design. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Inverse problems

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A Beam-Steering Broadband Microstrip Antenna with High Isolation

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Chinese Journal of Electronics 2023年第2期32卷 325-333页

作者： JIANG Zhaoneng SHA Yongxin NIE Liying XUAN Xiaofeng School of Computer and Information Hefei University of Technology School of Electronic Science and Applied Physics Hefei University of Technology

In this paper, a 4.2–7.2 GHz(52.6%)beam-steering microstrip antenna was proposed. The proposed antenna consists of three tapered slots and *** three radiation directions of the antenna on the plane are independent of each other, and the three feeds correspond to the three radiation structures. Symmetry isolation trenches are introduced to improve isolation between different ports. Radiation pattern simulation and measurement show horizontal beam steering at the sampled frequencies of 4.2, 5, 6, and 7.2 GHz. The results shows that the overlapped beam of the three ports in the Eplane and H-plane can cover more than 200 degrees and 60degrees, respectively. Apart from the capability of beamsteering, high isolation(more than 28 d B) of the proposed antenna in the operating band is obtained.

关键词： Antenna measurements Mutual coupling Slot antennas Microstrip antennas Antenna feeds Frequency measurement Broadband antennas

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Correlation-aware probabilistic data summarization for large-scale multi-block scientific data visualization

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Computational Visual Media 2023年第3期9卷 513-529页

作者： Yang Yang Kecheng Lu Yu Wu Yunhai Wang Yi Cao Institute of Applied Physics and Computational Mathematics Beijing 100094China School of Computer Science and Technology Shandong UniversityQingdao 266237China

In this paper,we propose a correlationaware probabilistic data summarization technique to efficiently analyze and visualize large-scale multi-block volume data generated by massively parallel scientific *** core of our technique is correlation modeling of distribution representations of adjacent data blocks using copula functions and accurate data value estimation by combining numerical information,spatial location,and correlation distribution using Bayes’*** effectively preserves statistical properties without merging data blocks in different parallel computing nodes and repartitioning them,thus significantly reducing the computational ***,this enables reconstruction of the original data more accurately than existing *** demonstrate the effectiveness of our technique using six datasets,with the largest having one billion grid *** experimental results show that our approach reduces the data storage cost by approximately one order of magnitude compared to state-of-the-art methods while providing a higher reconstruction accuracy at a lower computational cost.

关键词： correlation-awareness large-scale data multi-block methods probabilistic data summarization

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