Enhancing Generative Class Incremental Learning Performance With a Model Forgetting Approach by Taro Togo, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama

“…GCIL is one of the hot topics in the field of computer vision, and it is considered one of the important tasks in society as one of the continual learning approaches for generative models. …”
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Sound Radiation by a Cylindrical Open Cavity with a Surface Source at the Bottom by Krzysztof SZEMELA

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An integer ambiguity clustering estimator for real-time precise point positioning by Kunlun Zhang, Jianghui Geng, Guangcai Li, Jiang Guo

“…We selected 115 multi-GNSS stations worldwide and carried out 22 days of continuous real-time PPP-AR. It is found that IACE improves the computational efficiency across various ambiguity dimensions compared to classic partial ambiguity resolution (PAR) and BIE, while improving the positioning precision over the float solution by 26.1%, 10.4%, and 5.6% in the east, north, and up components, respectively, overall comparable to the PAR and BIE. …”
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Controle de estoque por revisão contínua e revisão periódica: uma análise comparativa utilizando simulação Continuous and periodic review inventory control: a comparative analysis... by Hobed Rosa, Sérgio Fernando Mayerle, Mirian Buss Gonçalves

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Timely post-discharge medication reviews to Improve Continuity—the Transitions Of Care stewardship (TIC TOC) study in rural and regional Australia: a parallel-group randomised cont... by Sepehr Shakib, Manya Angley, Jonathan Penm, Charley Budgeon, Kim Nguyen, Rebekah Jane Moles, Faye McMillan, Rohan A Elliott, Paul Yates, Katie Phillips, Jenny Chen, Stephen Ross Carter, Kingston Yeung, Deirdre Criddle, Deborah Rigby, Frank Mario Sanfilippo, Jerry Yik, Deborah Hawthorne, Cristen Fleming, Anna Packer, Linda Krogh, Simon K Poon, Brett Chambers, Shania Liu, Fatemeh Emadi, Klaudia Englezos, Ganga Ratnanayagam, Michelle Penm, Andrew Hawthorne, Alexander Khlentzos, Jilian Khlentzos

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Wearable Sensor-Based Behavioral User Authentication Using a Hybrid Deep Learning Approach with Squeeze-and-Excitation Mechanism by Sakorn Mekruksavanich, Anuchit Jitpattanakul

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Solving Weighted Orthogonal Procrustes Problems via a Projected Gradient Method by H. F. Oviedo Leon, S. Guerrero

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Waveguide-Integrated Plasmonic Photodetectors and Activation Function Units With Phase Change Materials by Jacek Gosciniak

“…With a rapidly growing amount of data generated and processed, a search for more efficient components and architectures such as neuromorphic computing that can perform increasingly complex operations in more efficient way continue. …”
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An survey on application of artificial intelligence in 5G system by Jianwu ZHANG, Luxin WANG, Lingfen SUN, Qianye ZHANG, Hangguan SHAN

“…With the continuous development of 5G, the era of the internet of everything is coming.Problems such as massive device connections, massive application requests, ultra-high network load and complex dynamic network environment pose great challenges to the optimization of 5G systems in the context of the internet of everything.Facing these challenges, artificial intelligence (AI) shows its unique advantages.Firstly, the advantages of deep learning driven AI algorithms in 5G system compared with conventional algorithms were briefly introduced.Then, the application of AI algorithms in multi-access edge computing (MEC) and mmWave massive multiple-input multiple-output (MIMO) system were described in detail, with advantages and disadvantages of each method being compared and analyzed.Finally, according to the existing research, the shortcomings of AI algorithms in 5G application scenarios were summarized and the future research directions were forecasted.…”
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Research on location privacy protection of mobile terminals for maritime monitoring sensor networks by Xin SU, Su JIANG, Yiqing ZHOU

“…Mobile edge computing can support various maritime applications with high reliability and low delay.However, many security problems in computing task offloading exist.The risk of location privacy leakage of maritime mobile terminals during task offloading was analyzed and quantified.The related location privacy protection model was established and a dynamic cache and spatial cloaking-based location privacy protection (DS-LPP) algorithm was proposed.Simulation results show that DS-LPP algorithm has better performance of constructing anonymous space and selecting relay node than traditional algorithms while protecting the location privacy of maritime mobile terminals.Therefore, the DS-LPP algorithm can be effectively applied to maritime monitoring sensor network with relatively scanty communication and computing resources, and ensure the continuity of location privacy protection.…”
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Edge-Version of Fault-Tolerant Resolvability in Networks by Muhammad Faheem, Muhammad Ahmad, Zohaib Zahid, Muhammad Javaid, Mamo Abebe Ashebo

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Towards Efficient HPC: Exploring Overlap Strategies Using MPI Non-Blocking Communication by Yuntian Zheng, Jianping Wu

“…As high-performance computing (HPC) platforms continue to scale up, communication costs have become a critical bottleneck affecting overall application performance. …”
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Evaluation of quantum contouring algorithms for treatment planning on MR abdominal images by Rachel Glenn, Tucker Netherton, Adrian Celaya, Adrian Celaya, Mohamed Eltaher, Beatrice Riviere, Eugene J. Koay, Eugene J. Koay, David Fuentes, David Fuentes

“…IntroductionQuantum computing is increasingly being investigated for integration into medical radiology and healthcare applications worldwide. …”
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Optimal features assisted multi-attention fusion for robust fire recognition in adverse conditions by Inam Ullah, Nada Alzaben, Yousef Ibrahim Daradkeh, Mi Young Lee

“…However, high false alarm rates, shallow-layered networks, and poor recognition in challenging environments continue to hinder their practical deployment. To address these limitations, we introduce the Attention-Enhanced Fire Recognition Network (AEFRN). …”
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Personalized Clustering for Emotion Recognition Improvement by Laura Gutiérrez-Martín, Celia López-Ongil, Jose M. Lanza-Gutiérrez, Jose A. Miranda Calero

“…Emotion recognition through artificial intelligence and smart sensing of physical and physiological signals (affective computing) is achieving very interesting results in terms of accuracy, inference times, and user-independent models. …”
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Privacy-Preserving Approach for Early Detection of Long-Lie Incidents: A Pilot Study with Healthy Subjects by Riska Analia, Anne Forster, Sheng-Quan Xie, Zhiqiang Zhang

“…Real-time deployment on a Raspberry Pi 5 demonstrated the system is capable of accurately detecting long-lie incidents based on continuous monitoring over 15 min, with minimal posture variation; (4) Conclusion: The proposed system introduces a novel approach to long-lie detection by integrating privacy-aware sensing, interpretable posture-based features, and efficient edge computing. …”
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A 3D Model-Based Framework for Real-Time Emergency Evacuation Using GIS and IoT Devices by Noopur Tyagi, Jaiteg Singh, Saravjeet Singh, Sukhjit Singh Sehra

“…The proposed framework incorporates federated learning (FL) along with edge computing and Internet of Things (IoT) devices to achieve accurate floor-level localization and navigation. …”
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A Computational Approach to Increasing the Antenna System’s Sensitivity in a Doppler Radar Designed to Detect Human Vital Signs in the UHF-SHF Frequency Ranges by David Vatamanu, Simona Miclaus

“…The antenna–target system is modeled in the computational space in each new situation considered. …”
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COVID-19 messenger ribonucleic acid vaccination and abnormal radiopharmaceutical uptake in the axilla visualized on 68Ga-DOTATATE positron-emission tomography/computed tomography by Joshua Weissman, Twyla Bartel

“…As COVID-19 vaccination rates continue to rise, it is becoming increasingly important to understand diagnostic imaging associations' resultant from the vaccines. …”
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Discrete variable 3D models in Computer extended Descriptive Geometry (CeDG): Building of polygonal sheet-metal elbows and comparison against CAD by Manuel Prado-Velasco, Laura García-Ruesgas

“…The Computer extended Descriptive Geometry (CeDG) is as a novel approach based on Descriptive Geometry to build 3D models within the framework provided by Dynamic Geometry Software tools. …”
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