检索结果-内蒙古大学图书馆

A New Paradigm of User-Centric Wireless Communication Driven by Large Language Models

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Ding, Kuiyuan Guo, Caili Yang, Yang Hu, Wuxia Eldar, Yonina C. Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Beijing Laboratory of Advanced Information Net works School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot7610001 Israel

The next generation of wireless communications seeks to deeply integrate artificial intelligence (AI) with user-centric communication networks, with the goal of developing AI-native networks that more accurately address user requirements. The rapid development of large language models (LLMs) offers significant potential in realizing these goals. However, existing efforts that leverage LLMs for wireless communication often overlook the considerable gap between human natural language and the intricacies of real-world communication systems, thus failing to fully exploit the capabilities of LLMs. To address this gap, we propose a novel LLM-driven paradigm for wireless communication that innovatively incorporates the nature language to structured query language (NL2SQL) tool. Specifically, in this paradigm, user personal requirements is the primary focus. Upon receiving a user request, LLMs first analyze the user intent in terms of relevant communication metrics and system parameters. Subsequently, a structured query language (SQL) statement is generated to retrieve the specific parameter values from a high-performance real-time database. We further utilize LLMs to formulate and solve an optimization problem based on the user request and the retrieved parameters. The solution to this optimization problem then drives adjustments in the communication system to fulfill the user’s requirements. To validate the feasibility of the proposed paradigm, we present a prototype system. In this prototype, we consider user-request centric semantic communication (URC-SC) system in which a dynamic semantic representation network at the physical layer adapts its encoding depth to meet user requirements, such as improved data transmission quality or reduced data transmission latency. Additionally, two LLMs are employed to analyze user requests and generate SQL statements, respectively. Simulation results demonstrate the effectiveness of the prototype in personalizing and addressing user r

关键词： Structured Query Language

Analysing the impact of COVID-19 outbreak and economic policy uncertainty on stock markets in major affected economies

学校读者我要写书评

暂无评论

Analysing the impact of COVID-19 outbreak and economic polic...

6th Smart Cities Symposium (SCS 2022)

作者： A. Matuka S. S. Asafo G. O. Eweke P. Mishra S. Ray M. Abotaleb T. Makarovskikh A.A. Alhussan A.A. Abdelhamid E.M. El-Kenawy P. Dutta S. Chowdhury University of Macerata Department of Economics and Law Macerata Italy Department of Banking & Finance Niger Delta University Amassoma Nigeria College of Agriculture J.N.K.V.V. Powarkheda India Centurion University of Technology and Management Paralakhemundi India Department of System Programming South Ural State University Chelyabinsk Russia Department of Computer Sciences College of Computer and Information Sciences Princess Nourah bint Abdulrahman University Riyadh Saudi Arabia Department of Computer Science Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Department of Communications and Electronics Delta Higher Institute of Engineering and Technolog School of Engineering and Technology Amity University Kolkata Kolkata India MCA Department Sri Venkateshwara College of Engineering and Technology Chittoor India

The covid-19 pandemic and Economic Policy Uncertainty resulting from the shutdown of production, withdrawal of investments, enforcement of lockdowns and quarantines globally, have been directly affecting stock markets worldwide. This study is thus an attempt to analyse the impact of the COVID-19 pandemic on stock market behaviour in major affected economies. Moreover, the time frame was extended by using current data which investigate the impact of the virus during the boom and the blast phase in the country's most hit by the pandemic crisis such as China, Italy, UK and US. The frequency of the data is daily, and it dates from 3 January 2020 up to 10 February 2021. The considered time framework will give a deep insight into how stock markets behave in the case of an exogenous shock. The Dickey-Fuller Augmented Unit Root Test indicates that all the variables are stationary at first difference, which is one of the main conditions to have robust result, and the ARCH-LM test for the heteroskedasticity of the residuals, which show that all the probability values are significant, rejecting the null hypothesis of no ARCH effect. Based on the results of GARCH (1,1), we conclude that the change in stock markets volatility is positive and significant in China, Italy, UK and USA. This suggests that the impacts of COVID-19 outbreak and economic policy uncertainty on Stock Markets are a significant and Homogeneous across the studied countries, and the shock on FTSE Italia All Share has the longest time to vanish which makes it the riskiest to invest during this period, while the shock on SP500 USA has the shortest time to disappear meaning that it is safest Stock Market in this study. These findings have significant implications for policymakers, institutional and individual investors and Financial Markets analysts.

关键词：

[Retracted] IOT and Blockchain-Based Cloud Model for Secure Data Transmission for Smart City

学校读者我要写书评

暂无评论

Security and Communication Networks 2023年第1期2023卷

作者： Liwa H. Al-Farhani Yahya Alqahtani Hamdan Ali Alshehri R. John Martin Sachin Lalar Rituraj Jain System Analysis Control and Information Processing Academy of Engineering RUDN University Moscow Russiarudn.ru Faculty of Computer Science and Information Technology Jazan University Saudi Arabiajazanu.edu.sa Department of Computer Science and Applications Kurukshetra University Kurukshetra Indiakuk.ac.in Department of Electrical and Computer Engineering Wollega University Nekemte Ethiopiawollegauniversity.edu.et

The widespread use of the Internet of Things (IoT) technology has both good and bad things about it. There must be a full and reliable security system in place for the Internet of Things so that things can work together in a safe way and intrusions cannot happen. There are now many more ways to keep the Internet of Things safe, thanks to a detecting system. As machine learning and deep learning technologies have become better, a lot of good intrusion detection systems have been made. This kind of study is covered. These two types of security are compared in this study. The current machine-based intrusion detection system is broken down into more detailed categories based on detection technology, data source, architecture, and operating method. These categories are as follows: It is talked about how IoT security will grow in the future and how to understand its intrusion detection system too. In this paper, a cloud-based blockchain security model has been presented for secure data transmission over IoT.

关键词：

ForgeEDA: A Comprehensive Multimodal Dataset for Advancing EDA

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Shi, Zhengyuan Li, Zeju Ma, Chengyu Zhou, Yunhao Zheng, Ziyang Liu, Jiawei Pan, Hongyang Zhou, Lingfeng Li, Kezhi Zhu, Jiaying Yan, Lingwei He, Zhiqiang Xue, Chenhao Jiang, Wentao Yang, Fan Sun, Guangyu Yang, Xiaoyan Chen, Gang Shi, Chuan Chu, Zhufei Yang, Jun Xu, Qiang Department of Computer Science and Engineering The Chinese University of Hong Kong Sha Tin Hong Kong Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China School of Computer Science Beijing University of Posts and Telecommunications Beijing China School of Microelectronics State Key Laboratory of Integrated Chips and System Fudan University Shanghai China School of Electronic and Information Engineering Hangzhou Dianzi University Hangzhou China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China School of Integrated Circuits Peking University Beijing China School of Intergrated Circuits Southeast University Nanjing China National Center of Technology Innovation for EDA Nanjing China

We introduce ForgeEDA, an open-source comprehensive circuit dataset across various categories. ForgeEDA includes diverse circuit representations such as Register Transfer Level (RTL) code, Post-mapping (PM) netlists, And-Inverter Graphs (AIGs), and placed netlists, enabling comprehensive analysis and development. We demonstrate ForgeEDA’s utility by benchmarking state-of-the-art EDA algorithms on critical tasks such as Power, Performance, and Area (PPA) optimization, highlighting its ability to expose performance gaps and drive advancements. Additionally, ForgeEDA’s scale and diversity facilitate the training of AI models for EDA tasks, demonstrating its potential to improve model performance and generalization. By addressing limitations in existing datasets, ForgeEDA aims to catalyze breakthroughs in modern IC design and support the next generation of innovations in EDA. © 2025, CC BY.

关键词： Open source software

Retraction notice to “Automation industry in cyber physical systems based on 4G IoT networks for operation controlling and monitoring management” [Optik 272 (2023) 170308]

学校读者我要写书评

暂无评论

Optik 2025年 333卷

作者： K.V. Mahesan Anupong Wongchai C. Tamizhselvan S. Manoj Kumar P. Vijayakumar Bharat Singh Dr. Ambedkar Institute of Technology Bangalore India Department of Agricultural Economy and Development Faculty of Agriculture Chiang Mai University Thailand Department of Data Science and Business System College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai Tamilnadu India Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore 641407 India School of Electronics Engineering Vellore Institute of Technology Chennai India Department of Mechanical Engineering GLA University Mathura UP India

A nonlinear neural network based on an analog DNA toehold mediated strand displacement reaction circuit

学校读者我要写书评

暂无评论

Nanoscale 2022年第17期14卷 6585-6599页

作者： Chengye Zou Qiang Zhang Changjun Zhou Wenyu Cao School of Mathematics and Statistics Anyang Normal University Anyang 455000 China. Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian 116024 China. zhangq@***. Informedia Electronic Co. Ltd Dalian University of Technology Dalian 116024 China. College of Mathematics and Computer Science Zhejiang Normal University Jinhua 321000 China. zhou-chang231@***. Institution of Information Management and Information system Dalian University of Technology Dalian 116024 China.

The DNA toehold mediated strand displacement reaction is one of the semi-synthetic biology technologies for next-generation computers. In this article, we present a framework for a novel nonlinear neural network based on an engineered biochemical circuit, which is constructed by several reaction modules including catalysis, degradation and adjustment reaction modules. The proposed neural network possesses an architecture that is similar to that of an error back propagation neural network, and is built of an input layer, hidden layer and output layer. As a proof of concept, we utilize this nonlinear neural network based on an analog DNA toehold mediated strand displacement reaction circuit to learn the standard quadratic form function and analyze the robustness of the nonlinear neural network toward DNA strand concentration detection, DNA strand displacement reaction rate and noise. Unlike in error back propagation neural networks, the adaptive behavior of this DNA molecular neural network system endows it with supervised learning capability. This investigation will highlight the potential of analog DNA displacement reaction circuits for implementing artificial intelligence.

关键词：

Efficient MedSAMs: Segment Anything in Medical Images on Laptop

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Ma, Jun Li, Feifei Kim, Sumin Asakereh, Reza Le, Bao-Hiep Nguyen-Vu, Dang-Khoa Pfefferle, Alexander Wei, Muxin Gao, Ruochen Lyu, Donghang Yang, Songxiao Purucker, Lennart Marinov, Zdravko Staring, Marius Lu, Haisheng Dao, Thuy Thanh Ye, Xincheng Li, Zhi Brugnara, Gianluca Vollmuth, Philipp Foltyn-Dumitru, Martha Cho, Jaeyoung Mahmutoglu, Mustafa Ahmed Bendszus, Martin Pflüger, Irada Rastogi, Aditya Ni, Dong Yang, Xin Zhou, Guang-Quan Wang, Kaini Heller, Nicholas Papanikolopoulos, Nikolaos Weight, Christopher Tong, Yubing Udupa, Jayaram K. Patrick, Cahill J. Wang, Yaqi Zhang, Yifan Contijoch, Francisco McVeigh, Elliot Ye, Xin He, Shucheng Haase, Robert Pinetz, Thomas Radbruch, Alexander Krause, Inga Kobler, Erich He, Jian Tang, Yucheng Yang, Haichun Huo, Yuankai Luo, Gongning Kushibar, Kaisar Amankulov, Jandos Toleshbayev, Dias Mukhamejan, Amangeldi Egger, Jan Pepe, Antonio Gsaxner, Christina Luijten, Gijs Fujita, Shohei Kikuchi, Tomohiro Wiestler, Benedikt Kirschke, Jan S. de la Rosa, Ezequiel Bolelli, Federico Lumetti, Luca Grana, Costantino Xie, Kunpeng Wu, Guomin Puladi, Behrus Martín-Isla, Carlos Lekadir, Karim Campello, Victor M. Shao, Wei Brisbane, Wayne Jiang, Hongxu Wei, Hao Yuan, Wu Li, Shuangle Zhou, Yuyin Wang, Bo AI Collaborative Centre University Health Network Department of Laboratory Medicine and Pathobiology University of Toronto Vector Institute Toronto Canada Peter Munk Cardiac Centre University Health Network Toronto Canada Toronto General Hospital Research Institute University Health Network Department of Computer Science University of Toronto University Health Network Vector Institute Toronto Canada University of Science Vietnam National University Ho Chi Minh City Viet Nam Institute of Computer Science University of Freiburg Freiburg Germany School of Medicine and Health Harbin Institute of Technology Harbin China Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Department of System and Control Engineering School of Engineering Institute of Science Tokyo Formerly Tokyo Institute of Technology Tokyo Japan Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia School of Cyberspace Hangzhou Dianzi University Hangzhou China Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Radiology and Clinical AI Department of Neuroradiology University Hospital Bonn Germany School of Biomedical Engineering Shenzhen University Shenzhen China School of Biological Science and Medical Engineering Southeast University Nanjing China Department of Urology Cleveland Clinic Cleveland United States Department of Computer Science University of Minnesota Minneapolis United St

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice. In this work, we organized the first international competition dedicated to promptable medical image segmentation, featuring a large-scale dataset spanning nine common imaging modalities from over 20 different institutions. The top teams developed lightweight segmentation foundation models and implemented an efficient inference pipeline that substantially reduced computational requirements while maintaining state-of-the-art segmentation accuracy. Moreover, the post-challenge phase advanced the algorithms through the design of performance booster and reproducibility tasks, resulting in improved algorithms and validated reproducibility of the winning solution. Furthermore, the best-performing algorithms have been incorporated into the open-source software with a user-friendly interface to facilitate clinical adoption. The data and code are publicly available to foster the further development of medical image segmentation foundation models and pave the way for impactful real-world applications. © 2024, CC BY-NC-SA.

关键词： Open source software

Distributed Nash Equilibrium Seeking in Coalition Games for Uncertain Euler-Lagrange systems With Application to USV Swarm Confrontation

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Yuwen, Cheng Wen, Guanghui Zhou, Jialing Luan, Meng Huang, Tingwen School of Automation Southeast University Nanjing210096 China State Key Laboratory of CNS/ATM Beijing Institute of Technology Beijing519088 China Department of System Science School of Mathematics Southeast University Nanjing211189 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen218055 China

In this paper, a coalition game with local and coupling constraints is studied for uncertain Euler-Lagrange (EL) systems subject to disturbances with unknown bounds. In the coalition game, each agent collaborates with other agents within the same coalition to optimize its coalition’s cost function while simultaneously competing against agents in other coalitions. Under a distributed framework where each agent has access only to its own action, cost function, and constraint parameters, a distributed strategy is proposed to seek the Nash equilibrium (NE). By combining adaptive methods and sign functions, model uncertainties and disturbances with unknown bounds in the EL system are compensated and suppressed, respectively. Furthermore, an integration of adaptive methods and consensus protocols is employed to update the Lagrange multipliers of both local and coupling constraints. A dynamic average consensus is employed to estimate the gradient of coalition function, while the leader-following protocol is adopted to estimate the actions of other agents. By leveraging Lyapunov theory, the NE is proven to be asymptotically stable. Moreover, an unmanned surface vehicle swarm confrontation is meticulously modeled and analyzed in the coalition game framework. A diverse array of tasks, including formation, encirclement, and interception, are systematically formulated. A numerical example demonstrates the effectiveness of the proposed algorithm. Copyright © 2025, The Authors. All rights reserved.

关键词： Lagrange multipliers

Unveiling the Role of Biological and Environmental Factors and the Piscivory in the Recruitment Success of Pikeperch (Stizostedion Lucioperca)

学校读者我要写书评

暂无评论

SSRN

SSRN 2024年

作者： Tesfaye, Million Jůza, Tomáš Šmejkal, Marek Soukalová, Katerina Bartoň, Daniel Blabolil, Petr Čech, Martin Hejzlar, Josef Prchalová, Marie Muška, Milan Tušer, Michal Kočvara, Luboš Sajdlová, Zuzana Draštík, Vladislav Martinez, Carlos de Moraes, Karlos Ribeiro Říha, Milan Vašek, Mojmír Symonová, Radka Brabec, Marek Kubečka, Jan Souza, Allan T. Biology Centre of the Czech Academy of Sciences Institute of Hydrobiology Na Sádkách 7 České Budějovice370 05 Czech Republic Faculty of Fisheries and Protection of Waters South Bohemian Research Centre for Aquaculture and Biodiversity of Hydrocenoses University of South Bohemia in České Budějovice Zátiší 728/II Vodňany389 25 Czech Republic University of South Bohemia Faculty of Science Department of Ecosystem Biology Branišovská 1760a České Budějovice370 05 Czech Republic School of Biochemical Engineering Pontificia Universidad Católica de Valparaíso Av. Brasil 2085 Valparaíso2340000 Chile Institute of Computer Science Czech Academy of Sciences Prague182 00 Czech Republic Institute for Atmospheric and Earth System Research INAR Forest Sciences Faculty of Agriculture and Forestry University of Helsinki P.O. Box 27 00014 Finland

Pikeperch (Sander lucioperca) is an important fish species in Eurasian water bodies. However, its recruitment has declined in some lakes, necessitating a better understanding of its ecological process. In the first summer, young-of-the-year (YOY) pikeperch can be grouped into three sub-cohorts: extremely small (ES), ordinary fingerlings, and piscivorous. We analyzed 12 years of biotic and abiotic data collected between 2003 and 2022 at Lipno Reservoir (Czechia) to identify drivers of variability in the abundance of piscivorous YOY pikeperch and their impact on the new year class. Using the Bayesian horseshoe prior approach and linear regression, we observed that a higher abundance of ES conspecifics and YOY perch, coupled with increased densities of large cladocerans in July and August, positively impacted the abundance of piscivorous YOY. Additionally, August precipitation positively affected this sub-cohort. The abundance of 1+ pikeperch was positively influenced by the abundance of piscivorous and ordinary YOYs recorded in the preceding year. We concluded that all three sub-cohorts contribute to the recruitment success of pikeperch, with piscivorous and ordinary sub-cohorts having a more direct effect, while ES sub-cohorts indirectly enhance piscivory pikeperch. The study provides novel insight into factors influencing the recruitment success of pikeperch and aids forecasting capabilities. © 2024, The Authors. All rights reserved.

关键词： Reservoirs (water)