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39th International Symposium on Lattice Field Theory, LATTICE 2022

作者： Athenodorou, Andreas Bennett, Ed Lenz, Julian Papadopoullou, Elli Computation-based Science and Technology Research Center The Cyprus Institute Cyprus Swansea Academy of Advanced Computing Swansea University Fabian Way SwanseaSA1 8EN United Kingdom ATHENA Research Center Artemidos 6 & Epidavrou Marousi15125 Greece

Open science aims to make scientific research processes, tools and results accessible to all scientific communities, creating trust in science and enabling digital competences to be realized in research, leading to increased innovation. It provides standard and transparent pathways to conducting research and fosters best practices for collecting, analysing, preserving, sharing and reusing data, software, workflows and other outputs through collaborative networks. Open Science appears to be becoming the norm with its applications spanning throughout the whole research cycle of a project. The importance of making Open Science a reality is nowadays reflected in funding policies, research infrastructure and politics. In these proceedings we present the basic Open Science principles explaining briefly best practices for materialising Open Science. Subsequently, we present the results of the landscaping survey of Open Science in the Lattice Gauge Theories community. Finally, we provide directions in which the Lattice Gauge Theory community could move in order to enhance Openness and FAIRness (Findability, Accessibility, Interoperability, Reusability) in Science. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).

关键词： Reusability

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Online Learning to Cache and Recommend in the Next Generation Cellular Networks

IEEE Transactions on Machine Learning in Communications and ...

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IEEE Transactions on Machine Learning in Communications and Networking 2024年 2卷 511-525页

作者： Tharakan, Krishnendu S Bharath, B.N. Bhatia, Vimal Queen's University School of Computing KingstonONK7L 3N6 Canada Dharwad580011 India Indian Institute of Technology Indore Department of Electrical Engineering Center for Advanced Electronics Indore453552 India University of Hradec Králové Faculty of Informatics and Management Hradec Králové500 03 Czech Republic Soochow University School of Electronic and Information Engineering Suzhou215006 China

An efficient caching can be achieved by predicting the popularity of the files accurately. It is well known that the popularity of a file can be nudged by using recommendation, and hence it can be estimated accurately leading to an efficient caching strategy. Motivated by this, in this paper, we consider the problem of joint caching and recommendation in a 5G and beyond heterogeneous network. We model the influence of recommendation on demands by a Probability Transition Matrix (PTM). The proposed framework consists of estimating the PTM and use them to jointly recommend and cache the files. In particular, this paper considers two estimation methods namely a) Bayesian estimation and b) a genie aided Point estimation. An approximate high probability bound on the regret of both the estimation methods are provided. Using this result, we show that the approximate regret achieved by the genie aided Point estimation approach is mathcal {O}(T{2/3} sqrt {log T}) while the Bayesian estimation method achieves a much better scaling of mathcal {O}(sqrt {T}). These results are extended to a heterogeneous network consisting of M small base stations (SBSs) with a central macro base station. The estimates are available at multiple SBSs, and are combined using appropriate weights. Insights on the choice of these weights are provided by using the derived approximate regret bound in the multiple SBS case. Finally, simulation results confirm the superiority of the proposed algorithms in terms of average cache hit rate, delay and throughput. © 2023 CCBY.

关键词： Heterogeneous networks

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Modeling and Clustering of Parabolic Granular Data

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3728-3742页

作者： Tang, Yiming Gao, Jianwei Pedrycz, Witold Hu, Xianghui Xi, Lei Ren, Fuji Hu, Min Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei230601 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2V4 Canada Hefei University of Technology School of Computer and Information Hefei230601 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Polish Academy of Sciences Systems Research Institute Warsaw00-901 Poland Istinye University Research Center of Performance and Productivity Analysis Istanbul34010 Turkey Southeast University School of Computer Science and Engineering Nanjing211189 China University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu611731 China

At present, there exist some problems in granular clustering methods, such as lack of nonlinear membership description and global optimization of granular data boundaries. To address these issues, in this study, revolving around the parabolic granular data, we propose an overall architecture for parabolic granular modeling and clustering. To begin with, novel coverage and specificity functions are established, and then a parabolic granular data structure is proposed. The fuzzy c-means (FCM) algorithm is used to obtain the numeric prototypes, and then particle swarm optimization (PSO) is introduced to construct the parabolic granular data from the global perspective under the guidance of principle of justifiable granularity (PJG). Combining the advantages of FCM and PSO, we propose the parabolic granular modeling and optimization (PGMO) method. Moreover, we put forward attribute weights and sample weights as well as a distance measure induced by the Gaussian kernel similarity, and then come up with the algorithm of weighted kernel fuzzy clustering for parabolic granularity (WKFC-PG). In addition, the assessment mechanism of parabolic granular clustering is discussed. In summary, we set up an overall architecture including parabolic granular modeling, clustering, and assessment. Finally, comparative experiments on artificial, UCI, and high-dimensional datasets validate that our overall architecture delivers a good improvement over previous strategies. The parameter analysis and time complexity are also given for WKFC-PG. In contrast with related granular clustering algorithms, it is observed that WKFC-PG performs better than other granular clustering algorithms and has superior stability in handling outliers, especially on high-dimensional datasets. © 2020 IEEE.

关键词： Fuzzy clustering

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Algorithmic fairness in social context

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BenchCouncil Transactions on Benchmarks, Standards and Evaluations 2023年第3期3卷 100137-100137页

作者： Huang, Yunyou Liu, Wenjing Gao, Wanling Lu, Xiangjiang Liang, Xiaoshuang Yang, Zhengxin Li, Hongxiao Ma, Li Tang, Suqin Key Lab of Education Blockchain and Intelligent Technology Ministry of Education Guangxi Normal University No. 15 Yucai Road Qixing District Guangxi Guilin541004 China Research Center for Advanced Computer Systems Institute of Computing Technology Chinese Academy of Sciences No. 6 Kexueyuan South Road Haidian District Beijing 100190 China

Algorithmic fairness research is currently receiving significant attention, aiming to ensure that algorithms do not discriminate between different groups or individuals with similar characteristics. However, with the popularization of algorithms in all aspects of society, algorithms have changed from mere instruments to social infrastructure. For instance, facial recognition algorithms are widely used to provide user verification services and have become an indispensable part of many social infrastructures like transportation, health care, etc. As an instrument, an algorithm needs to pay attention to the fairness of its behavior. However, as a social infrastructure, it needs to pay even more attention to its impact on social fairness. Otherwise, it may exacerbate existing inequities or create new ones. For example, if an algorithm treats all passengers equally and eliminates special seats for pregnant women in the interest of fairness, it will increase the risk of pregnant women taking public transport and indirectly damage their right to fair travel. Therefore, algorithms have the responsibility to ensure social fairness, not just within their operations. It is now time to expand the concept of algorithmic fairness beyond mere behavioral equity, assessing algorithms in a broader societal context, and examining whether they uphold and promote social fairness. This article analyzes the current status and challenges of algorithmic fairness from three key perspectives: fairness definition, fairness dataset, and fairness algorithm. Furthermore, the potential directions and strategies to promote the fairness of the algorithm are proposed. © 2023 The Authors

关键词： Face recognition

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Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

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Computer Systems Science & Engineering 2023年第10期47卷 553-574页

作者： Adnan Hasan Bdair Aighuraibawi Selvakumar Manickam Rosni Abdullah Zaid Abdi Alkareem Alyasseri Ayman Khallel Dilovan Asaad Zebari Hussam Mohammed Jasim Mazin Mohammed Abed Zainb Hussein Arif National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaPenang11800Malaysia Baghdad College of Economic Sciences University BaghdadIraq School of Computer Sciences Universiti Sains MalaysPenang11800Malaysia Information Technology Research and Development Center University of KufaNajafIraq College of Engineering University of Warith Al-AnbiyaaKarbalaIraq Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Business Administration College of Administration and Financial SciencesImam Ja’afar Al-Sadiq UniversityBaghdad10001Iraq College of Computer Science and Information Technology University of AnbarRamadi AnbarIraq Department of Computer Science College of ScienceNawroz UniversityDuhok42001Kurdistan RegionIraq

Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the ***6 has introduced new features like Neighbour Discovery Protocol(NDP)and Address Auto-configuration ***6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol(ICMPv6).IPv6 is vulnerable to numerous attacks like Denial of Service(DoS)and Distributed Denial of Service(DDoS)which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial ***,an Intrusion Detection System(IDS)is a monitoring system of the security of a network that detects suspicious activities and deals with amassive amount of data comprised of repetitive and inappropriate features which affect the detection rate.A feature selection(FS)technique helps to reduce the computation time and complexity by selecting the optimum subset of *** paper proposes a method for detecting DDoS flooding attacks(FA)based on ICMPv6 messages using a Binary Flower PollinationAlgorithm(BFPA-FA).The proposed method(BFPA-FA)employs FS technology with a support vector machine(SVM)to identify the most relevant,influential ***,The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack *** results show that the proposed method BFPAFA achieved the best accuracy rate(97.96%)for the ICMPv6 DDoS detection with a reduced number of features(9)to half the total(19)*** proven proposed method BFPA-FAis effective in the ICMPv6 DDoS attacks via IDS.

关键词： IPv6 ICMPv6 DDoS feature selection flower pollination algorithm anomaly detection

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Reproducibility and Open Science in Lattice Quantum Field Theory

arXiv

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arXiv 2025年

作者： Bennett, Ed. Athenodorou, Andreas Chisholm, Louise Hasenfratz, Anna Urbach, Carsten Swansea Academy of Advanced Computing Swansea University Bay Campus Fabian Way SwanseaSA1 8EN United Kingdom Computation-based Science and Technology Research Center The Cyprus Institute 20 Kavafi Str. Nicosia2121 Cyprus Advanced Research Computing Centre University College London Gower Street LondonWC1E 6BT United Kingdom Department of Physics University of Colorado BoulderCO80309 United States Bethe Center for Theoretical Physics Universität Bonn Bonn53115 Germany

Reproducibility and Open Science are increasingly discussed as essential aspects of the research process. While there are areas where the Lattice community has been ahead of the curve with respect to the broader research world in this space, including early adoption of open publications via the arXiv, and the introduction of the International Lattice Data Grid in the 2000s, there are other areas where lattice practitioners could benefit from practices already adopted in other disciplines. In this Contribution, we report the outcomes of a panel discussion on this topic at the Lattice 2024 conference;after a discussion on motivations for work in this space, and introductory discussions of the relevant experiences of the panelists, we provide summaries of answers to the questions posed by the audience in the panel. © 2025, CC BY.

关键词： Lattice theory

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Phase Reentrances and Solid Deformations in Confined Colloidal Crystals

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Physical Review Letters 2024年第1期132卷 018202-018202页

作者： Xiaoxia Li Huang Fang Krongtum Sankaewtong Minhuan Li Yanshuang Chen Jiping Huang Ran Ni Hajime Tanaka Peng Tan State Key Laboratory of Surface Physics and Department of Physics Fudan University Shanghai 200433 China Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai 200433 China Chemical Engineering School of Chemical and Biomedical Engineering Nanyang Technological University 62 Nanyang Drive 637459 Singapore Department of Fundamental Engineering Institute of Industrial Science University of Tokyo 4-6-1 Komaba Meguro-ku Tokyo 153-8505 Japan Research Center for Advanced Science and Technology University of Tokyo 4-6-1 Komaba Meguro-ku Tokyo 153-8904 Japan

A simple geometric constraint often leads to novel, complex crystalline phases distinct from the bulk. Using thin-film charge colloidal crystals, a model system with tunable interactions, we study the effects of geometric constraints. Through a combination of experiments and simulations, we systematically explore phase reentrances and solid deformation modes concerning geometrical confinement strength, identifying two distinct categories of phase reentrances below a characteristic layer number, Nc: one for bcc bulk-stable and another for fcc bulk-stable systems. We further verify that the dominant thermodynamic origin is the nonmonotonic dependence of solids’ free energy on the degree of spatial confinement. Moreover, we discover transitions in solid deformation modes between interface-energy and bulk-energy dominance: below a specific layer number, Nk, geometric constraints generate unique soft deformation modes adaptive to confinement. These findings on the N-dependent thermodynamic and kinetic behaviors offer fresh insights into understanding and manipulating thin-film crystal structures.

关键词： Phase transitions by order Colloidal crystal Colloids

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Pre-Equalization Aided Grant-Free Massive Access in Massive MIMO System

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IEEE Transactions on Vehicular technology 2025年

作者： Wang, Yueqing Mei, Yikun Gao, Zhen Wan, Ziwei Ning, Boyu Mi, De Muhaidat, Sami School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology MIIT Key Laboratory of Complex-Field Intelligent Sensing Beijing100081 China Yangtze Delta Region Academy Jiaxing314019 China Beijing Institute of Technology Advanced Technology Research Institute Jinan250307 China University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Birmingham City University School of Computing and Digital Technology BirminghamB55JU United Kingdom Khalifa University KU 6 G Research Center Department of Computer and Information Engineering Abu Dhabi United Arab Emirates

The spatial diversity and multiplexing advantages of massive multi-input-multi-output (mMIMO) can significantly improve the capacity of massive non-orthogonal multiple access (NOMA) in machine type communications. However, state-of-the-art grant-free massive NOMA schemes for mMIMO systems require accurate estimation of random access channels to perform activity detection and the following coherent data demodulation, which suffers from excessive pilot overhead and access latency. To address this, we propose a pre-equalization aided grant-free massive access scheme for mMIMO systems, where an iterative detection scheme is conceived. Specifically, the base station (BS) firstly activates one of its antennas (i.e., beacon antenna) to broadcast a beacon signal, which facilitates the user equipment (UEs) to perform downlink channel estimation and pre-equalize the uplink random access signal with respect to the channels associated with the beacon antenna. During the uplink transmission stage, the BS detects UEs' activity and data by using the proposed iterative detection algorithm, which consists of three modules: coarse data detection (DD), data-aided channel estimation (CE), and fine DD. In the proposed algorithm, the joint activity and DD is firstly performed based on the signals received by the beacon antenna. Subsequently, the DD is further refined by iteratively performing data-aided CE module and fine DD module using signals received by all BS antennas. Our simulation results demonstrate that the proposed scheme outperforms state-of-the-art mMIMO-based grant-free massive NOMA schemes with the same access latency. © 1967-2012 IEEE.

关键词： Channel estimation

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Open Science in Lattice Gauge Theory community

arXiv

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arXiv 2022年

作者： Athenodorou, Andreas Bennett, Ed Lenz, Julian Papadopoullou, Elli Computation-based Science and Technology Research Center The Cyprus Institute Cyprus Swansea Academy of Advanced Computing Swansea University Fabian Way SwanseaSA1 8EN United Kingdom ATHENA research center Artemidos 6 & Epidavrou 15125 Marousi Greece

关键词： Reusability

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Pre-Equalization Aided Grant-Free Massive Access in Massive MIMO System

arXiv

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arXiv 2025年

作者： Wang, Yueqing Mei, Yikun Gao, Zhen Wan, Ziwei Ning, Boyu Mi, De Muhaidat, Sami School of Information and Electronics Beijing Institute of Technology Beijing100081 China MIIT Key Laboratory of Complex-Field Intelligent Sensing Beijing Institute of Technology Beijing100081 China Jiaxing314019 China Advanced Technology Research Institute Beijing Institute of Technology Jinan250307 China National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu611731 China School of Computing and Digital Technology Birmingham City University BirminghamB55JU United Kingdom KU 6G Research Center Department of Computer and Information Engineering Khalifa University Abu Dhabi United Arab Emirates

The spatial diversity and multiplexing advantages of massive multi-input-multi-output (mMIMO) can significantly improve the capacity of massive non-orthogonal multiple access (NOMA) in machine type communications. However, state-of-the-art grant-free massive NOMA schemes for mMIMO systems require accurate estimation of random access channels to perform activity detection and the following coherent data demodulation, which suffers from excessive pilot overhead and access latency. To address this, we propose a pre-equalization aided grant-free massive access scheme for mMIMO systems, where an iterative detection scheme is conceived. Specifically, the base station (BS) firstly activates one of its antennas (i.e., beacon antenna) to broadcast a beacon signal, which facilitates the user equipment (UEs) to perform downlink channel estimation and pre-equalize the uplink random access signal with respect to the channels associated with the beacon antenna. During the uplink transmission stage, the BS detects UEs’ activity and data by using the proposed iterative detection algorithm, which consists of three modules: coarse data detection (DD), data-aided channel estimation (CE), and fine DD. In the proposed algorithm, the joint activity and DD is firstly performed based on the signals received by the beacon antenna. Subsequently, the DD is further refined by iteratively performing data-aided CE module and fine DD module using signals received by all BS antennas. Our simulation results demonstrate that the proposed scheme outperforms state-of-the-art mMIMO-based grant-free massive NOMA schemes with the same access latency. Simulation codes are provided to reproduce the results in this article: https://***/owenwang517/tvt-2025. Copyright © 2025, The Authors. All rights reserved.

关键词： Channel estimation

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