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arXiv 2021年

作者： Zhang, Nan Zhang, Guopeng Wang, Kezhi Yang, Kun School of Computer Science and Technology China University of Mining and Technology Xuzhou221116 China Department of Computer and Information Science Northumbria University NewcastleNE2 1XE United Kingdom School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Technology and Engineering Changchun Institute of Technology Changchun China

In this paper, a multi-user cooperative computing framework is applied to enable mobile users to utilize available computing resources from other neighboring users via direct communication links. An incentive scheme based on Bertrand game is proposed for the user to determine who and how to cooperate. We model the resource demand users as buyers who aim to use minimal payments to maximize energy savings, whereas resource supply users as sellers who aim to earn payments for their computing resource provision. A Bertrand game against buyer’s market is formulated. When the users have complete information of their opponents, the Nash equilibrium (NE) of the game is obtained in closed form, while in the case of incomplete information, a distributed iterative algorithm is proposed to find the NE. The simulation results verify the effectiveness of the proposed scheme. Copyright © 2021, The Authors. All rights reserved.

关键词： Game theory

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Email notifier using named entity extraction

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AIP Conference Proceedings 2023年第1期2523卷

作者： K. Anand M. Vijay Anand R. Saravanan 1Department Information Technology Center for Artificial Intelligence and Research Chennai Institute of Technology Chennai Tamil Nadu India 2Department of Computer Science and Engineering Saveetha Engineering College (Autonomous) Chennai Tamil Nadu India 3Department Information Technology Center for Artificial Intelligence and Research Chennai Institute of Technology Chennai Tamil Nadu India

Email plays an essential role in communication and its flexibility, simplicity, diversified types, and low cost of information in the modern world. Therefore handling out a large volume of emails takes are mark able amount of human power and time. To quickly extract the named entities from an email requires an automated solution. So we proposed a tool to extract named entities from emails. This solution incorporates the latest technologies like NLP (Natural Language Processing) and IR (information Retrieval). This would perform named entities extraction of email automatically organizes and notifies the user. The proposed mechanism can be used in many organizations. Named Entity Recognition (NER) will be a vital language processing tool for information retrieval from texts like newspapers, blogs, and emails. NER performs the classification of words and sensing the expression of text from unstructured data. Spa Cy may be a free, open-source python library for advanced language Processing. It is well known for production use and helps build the system that performs understanding of a text. It helps in information extraction, understanding the plans, and preprocesses the text for deep learning.

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Interference Management for Over-the-Air Federated Learning in Multi-Cell Wireless Networks

arXiv

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arXiv 2022年

作者： Wang, Zhibin Zhou, Yong Shi, Yuanming Zhuang, Weihua The School of Information Science and Technology ShanghaiTech University Shanghai201210 China Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai200050 China The University of Chinese Academy of Sciences Beijing100049 China The Department of Electrical and Computer Engineering University of Waterloo ONN2L 3G1 Canada

Federated learning (FL) over resource-constrained wireless networks has recently attracted much attention. However, most existing studies consider one FL task in single-cell wireless networks and ignore the impact of downlink/uplink intercell interference on the learning performance. In this paper, we investigate FL over a multi-cell wireless network, where each cell performs a different FL task and over-the-air computation (AirComp) is adopted to enable fast uplink gradient aggregation. We conduct convergence analysis of AirComp-assisted FL systems, taking into account the inter-cell interference in both the downlink and uplink model/gradient transmissions, which reveals that the distorted model/gradient exchanges induce a gap to hinder the convergence of FL. We characterize the Pareto boundary of the error-induced gap region to quantify the learning performance trade-off among different FL tasks, based on which we formulate an optimization problem to minimize the sum of error-induced gaps in all cells. To tackle the coupling between the downlink and uplink transmissions as well as the coupling among multiple cells, we propose a cooperative multi-cell FL optimization framework to achieve efficient interference management for downlink and uplink transmission design. Results demonstrate that our proposed algorithm achieves much better average learning performance over multiple cells than non-cooperative baseline schemes. Copyright © 2022, The Authors. All rights reserved.

关键词： Wireless networks

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Adaptive Geological Modelling and Its Application for Petroleum Reservoir Conditions

Adaptive Geological Modelling and Its Application for Petrol...

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2020 International Science and technology Conference on Earth Science, ISTCEarthScience 2020

作者： Ursegov, S.O. Zakharian, A.Z. Serkova, V.I. Center for Hydrocarbon Recovery Skolkovo Institute of Science and Technology Bolshoy Boulevard str. 30 - 1 Moscow121205 Russia Cervart Ltd 1-ya Yamskaya str. 3/7 Moscow127018 Russia Department of Computer Engineering Information Systems and Technologies Ukhta State Technical University Pervomaiskaya str. 13 Ukhta169300 Russia

The article discusses the difference between the adaptive geological model and the traditional deterministic one, which is based on the manual work of geologists in the pre-computer era. Today, the deterministic approach to modelling has outlived its usefulness. computer simulations use other methods. Therefore, it is necessary to break away from the deterministic tradition in order to move on. The adaptive geological model is a mathematical function, the purpose of which is not at all to display actual information about the structure of a petroleum reservoir as accurately as possible, but to predict its structure in undrilled zones. The adaptive approach proves that it is not necessary to obey the facts for a successful forecast. This is often even harmful, since the geological structure of the petroleum reservoir at the points where the wells are drilled is known without modelling. Just as in the regression analysis, it is not at all necessary that the function passes exactly through all the actual points, it is not necessary for the geological model of the petroleum reservoir to fully reproduce the actual data. This is the fundamental feature of the adaptive geological model. © Published under licence by IOP Publishing Ltd.

关键词： Petroleum reservoirs

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DeceFL:a principled fully decentralized federated learning framework

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National Science Open 2023年第1期2卷 35-51页

作者： Ye Yuan Jun Liu Dou Jin Zuogong Yue Tao Yang Ruijuan Chen Maolin Wang Chuan Sun Lei Xu Feng Hua Yuqi Guo Xiuchuan Tang Xin He Xinlei Yi Dong Li Guanghui Wen Wenwu Yu Hai-Tao Zhang Tianyou Chai Shaochun Sui Han Ding School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China Department of Applied Mathematics University of WaterlooWaterloo N2L 3G1Canada State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China School of Mathematical and Physical Sciences Wuhan Textile UniversityWuhan 430200China School of Electrical Engineering and Computer Science and Digital FuturesKTH Royal Institute of TechnologyStockholm 10044Sweden Shenyang Institute of Automation(SIA) Chinese Academy of SciencesShenyang 110169China School of Mathematics Frontiers Science Center for Mobile Information Communication and SecuritySoutheast UniversityNanjing 211189China Purple Mountain Laboratories Nanjing 211111China AVIC Chengdu Aircraft Industrial(Group)Co. Ltd.Chengdu 610091China

Traditional machine learning relies on a centralized data pipeline for model training in various applications;however,data are inherently *** a decentralized nature of databases presents the serious challenge for collaboration:sending all decentralized datasets to a central server raises serious privacy *** there has been a joint effort in tackling such a critical issue by proposing privacy-preserving machine learning frameworks,such as federated learning,most state-of-the-art frameworks are built still in a centralized way,in which a central client is needed for collecting and distributing model information(instead of data itself)from every other client,leading to high communication burden and high vulnerability when there exists a failure at or an attack on the central *** we propose a principled decentralized federated learning algorithm(DeceFL),which does not require a central client and relies only on local information transmission between clients and their neighbors,representing a fully decentralized learning *** has been further proven that every client reaches the global minimum with zero performance gap and achieves the same convergence rate O(1=T)(where T is the number of iterations in gradient descent)as centralized federated learning when the loss function is smooth and strongly ***,the proposed algorithm has been applied to a number of applications to illustrate its effectiveness for both convex and nonconvex loss functions,time-invariant and time-varying topologies,as well as IID and Non-IID of datasets,demonstrating its applicability to a wide range of real-world medical and industrial applications.

关键词： decentralized federated learning smart manufacturing control systems privacy

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Depth-Optimized Delay-Aware Tree (DO-DAT) for Virtual Network Function Placement

IEEE Networking Letters

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IEEE Networking Letters 2020年第3期2卷 149-153页

作者： Manias, Dimitrios Michael Hawilo, Hassan Jammal, Manar Shami, Abdallah Department of Electrical and Computer Engineering University of Western Ontario LondonN6A 3K7 Canada School of Information Technology York University TorontoM3J 1P3 Canada

With the constant increase in demand for data connectivity, network service providers are faced with the task of reducing their capital and operational expenses while ensuring continual improvements to network performance. Although Network Function Virtualization (NFV) has been identified as a solution, several challenges must be addressed to ensure its feasibility. In this letter, we present a machine learning-based solution to the Virtual Network Function (VNF) placement problem. This letter proposes the Depth-Optimized Delay-Aware Tree (DO-DAT) model by using the particle swarm optimization technique to optimize decision tree hyper-parameters. Using the Evolved Packet Core (EPC) as a use case, we evaluate the performance of the model and compare it to a previously proposed model and a heuristic placement strategy. © 2019 IEEE.

关键词： Network function virtualization

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A Survey on Large Language Models: Applications, Challenges, Limitations, and Practical Usage

TechRxiv

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TechRxiv 2025年

作者： Hadi, Muhammad Usman Al-Tashi, Qasem Qureshi, Rizwan Shah, Abbas Muneer, Amgad Irfan, Muhammad Zafar, Anas Shaikh, Muhammad Bilal Akhtar, Naveed Al-Garadi, Mohammed Ali Hassan, Syed Zohaib Shoman, Maged Wu, Jia Mirjalili, Seyedali Shah, Mubarak School of Engineering Ulster University BelfastBT15 1AP United Kingdom Department of Imaging Physics The University of Texas MD Anderson Cancer Center HoustonTX77030 United States Department of Electronics Engineering Mehran University of Engineering and Technology Jamshoro76062 Pakistan of Engineering Sciences and Technology Swabi23460 Pakistan Department of Computer Science National University of Computer and Emerging Sciences Karachi Pakistan Edith Cowan University 270 Joondalup Drive Joondalup PerthWA6027 Australia Computing and Information Systems The University of Melbourne 700 Swanston Street CarltonVIC3010 Australia Department of Biomedical Informatics Vanderbilt University Medical Center NashvilleTN United States Department of Civil Environmental and Construction Engineering The University of Central Florida OrlandoFL United States Centre for Artificial Intelligence Research and Optimization Torrens University Australia Fortitude Valley BrisbaneQLD4006 Australia University Research and Innovation Center Obuda University Budapest1034 Hungary Center for Research in Computer Vision The University of Central Florida OrlandoFL United States

Within the vast expanse of computerized language processing, a revolutionary entity known as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to comprehend intricate linguistic patterns and conjure coherent and contextually fitting responses. LLMs are a type of artificial intelligence (AI) that have emerged as powerful tools for a wide range of tasks, including natural language processing (NLP), machine translation, vision applications, and question-answering. This survey provides a comprehensive overview of LLMs, including their history, architecture, datasets, training methods, applications, challenges, and future prospects. We begin by discussing the fundamental concepts of generative AI and the architecture of generative pre-trained transformers (GPT). We then provide an overview of the history of LLMs, their evolution over time, and the different training methods. We also present benchmark dataset for training and fine-tuning and evaluating LLMs. We then discuss the wide range of tasks where they are used and also discuss applications of LLMs in different domains, including medicine, education, finance, engineering, agriculture, media, entertainment, politics, and law. We also discuss how LLMs are shaping the future of AI and their increasing role in scientific discovery, and how they can be used to solve real-world problems. Next, we explore the challenges associated with deploying LLMs in real-world scenarios, including ethical considerations, model biases, interpretability, privacy concerns, and computational resource requirements. This survey also highlights techniques for enhancing the robustness and controllability of LLMs and addressing bias, fairness, and quality issues in Generative AI. Finally, we conclude by highlighting the future of LLM research and the challenges that need to be addressed in order to make this technology more reliable and useful. This survey is intended to provide researchers, practitioners, and ent

关键词： Natural language processing systems

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Performance Analysis and Enhancement of Beamforming Training in 802.11ad

arXiv

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arXiv 2023年

作者： Wu, Wen Cheng, Nan Zhang, Ning Yang, Peng Aldubaikhy, Khalid Shen, Xuemin The Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada State Key Lab. of ISN The School of Telecommunications Engineering Xidian University Xian710071 China The Department of Computing Sciences Texas A&M University Corpus ChristiTX78412 United States The School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China The Department of Electrical Engineering Qassim University Buraydah52571 Saudi Arabia

Beamforming (BF) training is crucial to establishing reliable millimeter-wave communication connections between stations (STAs) and an access point. In IEEE 802.11ad BF training protocol, all STAs contend for limited BF training opportunities, i.e., associated BF training (A-BFT) slots, which results in severe collisions and significant BF training latency, especially in dense user scenarios. In this paper, we first develop an analytical model to evaluate the BF training protocol performance. Our analytical model accounts for various protocol components, including user density, the number of A-BFT slots, and protocol parameters, i.e., retry limit and contention window size. We then derive the average successful BF training probability, the BF training efficiency and latency. Since the derived BF training efficiency is an implicit function, to reveal the relationship between system parameters and BF training performance, we also derive an approximate expression of BF training efficiency. Theoretical analysis indicates that the BF training efficiency degrades drastically in dense user scenarios. To address this issue, we propose an enhancement scheme which adaptively adjusts the protocol parameters in tune with user density, to improve the BF training performance in dense user scenarios. Extensive simulations are carried out to validate the accuracy of the developed analytical model. In addition, simulation results show that the proposed enhancement scheme can improve the BF training efficiency by 35% in dense user scenarios. © 2023, CC BY-NC-SA.

关键词： Analytical models

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How precisely can we map blue ice in Antarctica 14

How precisely can we map blue ice in Antarctica

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Earth Resources and Environmental Remote Sensing/GIS Applications XIV 2023

作者： Jawak, Shridhar D. Wankhede, Sagar F Luis, Alvarinho J Pandit, Prashant H Convey, Peter Fretwell, Peter T. SIOS Knowledge Centre Svalbard Science Centre P.O. Box 156 Svalbard LongyearbyenN-9171 Norway Ministry of Earth Sciences Government of India Headland Sada Goa Vasco-da-Gama403804 India Department of Civil Engineering Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal576104 India Goa Gogol Margao403602 India Department of Information Engineering and Computer Science University of Trento Trento38123 Italy Institute for Earth Observation Eurac Research Viale Druso 1 Bolzano39100 Italy British Antarctic Survey Natural Environment Research Council High Cross Madingley Road CambridgeCB3 0ET United Kingdom Department of Zoology University of Johannesburg P.O. Box 524 Auckland Park2006 South Africa

ISBN: (纸本)9781510666979

Precise mapping of Blue Ice Regions (BIRs) in Antarctica can facilitate resource management during expeditions and help plan field investigations. Satellite-based BIR mapping was traditionally performed with large-swath, coarse to medium-resolution imagery. This study presents a comprehensive evaluation of four classification methods for mapping blue ice regions: Neural Network Classifier (NNC), Support Vector Machine (SVM), Maximum Likelihood (MXL), and Mahalanobis Distance (MD). Each method was trained and tested using a labeled dataset, and their performance was assessed based on Overall Accuracy (OA), Bias, and Average Root Mean Squared Error (RMSe). Among the methods, SVM stood out with exceptional performance, achieving an impressive OA of 92% and demonstrating a low bias of 1.27%. The SVM method also exhibited superior spatial accuracy, as indicated by an Average RMSe of 1978 m2, making it well-suited for precise delineation of blue ice regions. On the other hand, NNC and MXL demonstrated reasonable overall accuracy but exhibited higher spatial errors. MD showed potential for improvement in spatial accuracy, recording an Average RMSe of 3031 m2. Based on the evaluation, SVM emerged as the most effective technique for mapping blue ice regions, providing valuable insights for glaciological research and climate change studies. MODIS, Landsat, Sentinel, and Very High Resolution (VHR) data, such as WorldView-2 (WV-2), are recommended for mapping large, moderate-sized, and small-sized BIR patches, respectively. The inclusion of WV-2 data allows for accurate estimation of the maximum summer extent of BIRs across Antarctica, facilitating comprehensive assessments of their spatial distribution and dynamics. This research contributes to advancing the understanding of BIRs and their significance in climate and glaciological studies. The refined VHR blue ice map from the current study will be useful for future studies of mass balance, radiation budget, and regional clima

关键词： Mapping

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Optical properties of chiral three-dimensional photonic crystals

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Physical Review B 2023年第16期107卷 165307-165307页

作者： Shun Takahashi Takeyoshi Tajiri Yasuhiko Arakawa Satoshi Iwamoto Willem L. Vos Kyoto Institute of Technology Matsugasaki Sakyo-ku Kyoto 606-8585 Japan Department of Computer and Network Engineering The University of Electro-Communications 1-5-1 Chofugaoka Chofu Tokyo 182-8585 Japan Institute for Nano Quantum Information Electronics The University of Tokyo 4-6-1 Komaba Meguro-ku Tokyo 153-8505 Japan Research Center for Advanced Science and Technology The University of Tokyo 4-6-1 Komaba Meguro-ku Tokyo 153-8505 Japan Institute of Industrial Science The University of Tokyo 4-6-1 Komaba Meguro-ku Tokyo 153-8505 Japan Complex Photonic Systems (COPS) MESA+ Institute for Nanotechnology University of Twente P.O. Box 217 7500 AE Enschede The Netherlands

We perform a theoretical and numerical study of the optical properties of both direct and inverse three-dimensional (3D) chiral woodpile structures and a corresponding chiral Bragg stack, also known as a Reusch pile. We compute transmission spectra in the helical direction for finite crystals and photonic band structures, where we ensure the effective index of all structures to be the same. We find that both 3D structures show dual-band circular dichroism, where light with a particular circular polarization state—either left- or right-handed—reveals a broad stop band with major attenuation, whereas the other polarization state is transmitted nearly unimpeded. We observe such gaps in different frequency ranges with alternating handedness. The appearance of the circular-polarized gaps is successfully interpreted with a physical model wherein the circular polarization either corotates or counterrotates with the chiral structure, thereby effectively leading to a spatially dependent or a constant refractive index, and thus to the presence or absence of a gap. We find that the presence or absence of circularly polarized gaps is tuned by the transverse periods perpendicular to the chiral axis in both the 3D direct and inverse chiral woodpile crystal structures. The tunability of circular dichroism may find applications as on-chip sensors for circularly polarized light and in the on-chip detection of chiral molecules.

关键词： Photonic crystals Nanostructures Chiral symmetry Band structure methods Finite-difference time-domain method

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