检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Xie, Wenwen Sun, Geng Liu, Bei Li, Jiahui Wang, Jiacheng Du, Hongyang Niyato, Dusit Kim, Dong In The College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130012 China The College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore The College of Computing and Data Science Nanyang Technological University Singapore The Department of Electrical and Electronic Engineering The University of Hong Kong 999077 Hong Kong The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Emerging technologies in sixth generation (6G) of wireless communications, such as terahertz communication and ultra-massive multiple-input multiple-output, present promising prospects. Despite the high data rate potential of millimeter wave communications, millimeter wave (mmWave) communications in urban low altitude economy (LAE) environments are constrained by challenges such as signal attenuation and multipath interference. Specially, in urban environments, mmWave communication experiences significant attenuation due to buildings, owing to its short wavelength, which necessitates developing innovative approaches to improve the robustness of such communications in LAE networking. In this paper, we explore the use of an unmanned aerial vehicle (UAV)-carried intelligent reflecting surface (IRS) to support low altitude mmWave communication. Specifically, we consider a typical urban low altitude communication scenario where a UAV-carried IRS establishes a line-of-sight (LoS) channel between the mobile users and a source user (SU) despite the presence of obstacles. Subsequently, we formulate an optimization problem aimed at maximizing the transmission rates and minimizing the energy consumption of the UAV by jointly optimizing phase shifts of the IRS and UAV trajectory. Given the non-convex nature of the problem and its high dynamics, we propose a deep reinforcement learning-based approach incorporating neural episodic control, long short-term memory, and an IRS phase shift control method to enhance the stability and accelerate the convergence. Simulation results show that the proposed algorithm effectively resolves the problem and surpasses other benchmark algorithms in various performances. Copyright © 2025, The Authors. All rights reserved.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Review of monopoly models and implications for antitrust

引用

Procedia Computer Science 2022年 199卷 495-502页

作者： Mengyu Shang Yuan Li Zhiquan Qi University of Chinese Academy of Sciences Beijing 100190 PR China Research Center on Fictitious Economy & Data Science Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China University of Lyon Coactis MSH-14/16 av Berthelot 69363 Lyon France

In February 2021, the Ministry of Commerce Anti-monopoly Bureau of the People’s Republic of China released the Antitrust Guidelines for the Platform Economy Industry. This announcement signaled more governmental supervision and governance with Internet-related business. In practice, tech giants have been suffering administrative penalties one after another. This study presents a review and analysis of the research literature on the monopoly quantitative models, outlining the components and concluding the implications for anti-monopoly. This paper delineates three main research topics relating to the monopoly models within the literature: the oligopoly, monopolistic competition, and Internet platform monopoly. The Cournot model, Bertrand model, Stackelberg model, and Innovational model represent the oligopoly studies when a small group of large sellers dominates the market. We then discuss the monopolistic competition models as the Krugman model, D-S Model, and Lancaster Model. We pay particular attention to the platform economy to reflect the new era of monopoly with Marshall’s Dilemma. After the summary and comparison of the literature research trajectory, our analysis culminates in implications for antitrust: why Internet corporations and government meet this monopoly predicament, who are involved by monopoly policy, how consumers and market got impacted, and what countermeasures could be taken to improve the antitrust. This study contributes to overview the development of monopoly models and critically analyze based on the current antitrust situation and trend of platform economy integration. We should scrutinize the feasibility to adopt engrain view of monopoly mechanisms as benefit loss on the information technology economy. Therefore, this research raises the novel question and synergistic effects of monopoly.

关键词： Monopoly oligopoly models antitrust platform economy

来源：评论

学校读者我要写书评

暂无评论

Optimization Strategies for Client Drift in Federated Learning: A review 9th

Optimization Strategies for Client Drift in Federated Learni...

引用

9th International Conference on Information Technology and Quantitative Management, ITQM 2022

作者： Shi, Yong Zhang, Yuanying Xiao, Yang Niu, Lingfeng School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China College of Information Sciences and Technology University of Nebraska at Omaha NE68182 United States School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100190 China Faculty of Information Technology Beijing University of Technology Beijing100124 China

With the development of AI technology, there is an increasing awareness and concern about data privacy, and training data is becoming more and more fragmented. To make better use of this distributed data while ensuring privacy, federated learning is proposed, which can federate multiple distributed devices to train a machine learning model and does not exchange the raw training data. A key challenge in federated learning is that the distribution of data across clients is heterogeneous, which leads to client drift, that is, local model updates toward local optimal solutions, resulting in performance degradation of the global model. To address this problem, many federated learning algorithms have been proposed. In this paper, we provide a review of existing federated learning optimization strategies. In our opinion, the existing optimization strategies for client drift can be roughly classified into the following two categories: model aggregation and model training. We introduce these two categories separately. Finally, we present our perspectives on the future development. © 2022 The Author(s).

关键词： data privacy

来源：评论

学校读者我要写书评

暂无评论

An infrastructure with user-centered presentation data model for integrated management of materials data and services

引用

npj Computational Materials 2021年第1期7卷 779-786页

作者： Shilong Liu Yanjing Su Haiqing Yin Dawei Zhang Jie He Haiyou Huang Xue Jiang Xuan Wang Haiyan Gong Zhuang Li Hao Xiu Jiawang Wan Xiaotong Zhang Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology BeijingBeijingChina School of Computer and Communication Engineering University of Science and Technology BeijingBeijingChina Beijing Key Laboratory of Knowledge Engineering for Materials Science BeijingChina Corrosion and Protection Center University of Science and Technology BeijingBeijingChina Collaborative Innovation Center of Steel Technology University of Science and Technology BeijingBeijingChina National Materials Corrosion and Protection Data Center Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijingChina Institute for Advanced Materials and Technology University of Science and Technology BeijingBeijingChina Beijing Key Laboratory of Materials Genome Engineering University of Science and Technology BeijingBeijingChina

With scientific research in materials science becoming more data intensive and collaborative after the announcement of the Materials Genome Initiative,the need for modern data infrastructures that facilitate the sharing of materials data and analysis tools is compelling in the materials *** this paper,we describe the challenges of developing such infrastructure and introduce an emerging architecture with high *** call this architecture the Materials Genome engineering databases(MGED).MGED provides cloud-hosted services with features to simplify the process of collecting datasets from diverse data providers,unify data representation forms with user-centered presentation data model,and accelerate data discovery with advanced search *** also provides a standard service management framework to enable finding and sharing of tools for analyzing and processing *** describe MGED’s design,current status,and how MGED supports integrated management of shared data and services.

关键词： services service centered

来源：评论

学校读者我要写书评

暂无评论

Price change prediction of Ultra high frequency financial data based on temporal convolutional network

引用

Procedia Computer Science 2022年 199卷 1177-1183页

作者： Wei Dai Yuan An Wen Long School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 P.R. China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 P.R. China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 P.R. China

Through in-depth analysis of Ultra high frequency (UHF) stock price change data, more reasonable discrete dynamic distribution models are proposed in this paper. Firstly, we classify the price changes into several categories. Then, temporal convolutional network (TCN) is utilized to predict the conditional probability for each category. Furthermore, attention mechanism is added into the TCN architecture to model the time-varying distribution for stock price change data. Empirical research on constituent stocks of Chinese Shenzhen Stock Exchange 100 Index (SZSE 100) found that the TCN framework model and the TCN (attention) framework have a better overall performance than GARCH family models and the long short-term memory (LSTM) framework model for the description of the dynamic process of the UHF stock price change sequence. In addition, the scale of the dataset reached nearly 10 million, to the best of our knowledge, there has been no previous attempt to apply TCN to such a large-scale UHF transaction price dataset in Chinese stock market.

关键词： Temporal convolutional network Ultra high frequency Financial prediction

来源：评论

学校读者我要写书评

暂无评论

Retinal vascular segmentation algorithm based on Atrous attention U-net

Retinal vascular segmentation algorithm based on Atrous atte...

引用

Image Processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Yuchen Li Shenming Gu School of Information Engineering Zhejiang Ocean University Zhoushan China Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province Zhejiang Ocean University Zhoushan China

ISBN: (纸本)9781665464697

The segmentation of retinal blood vessels is helpful in the diagnosis of diabetes, hypertension and other diseases. However, retinal blood vessel segmentation has become a big problem due to different vessel sizes, complex vessel structures, and limited annotated data sets. Deep learning is widely used in the field of medical image segmentation, among which U-net is widely used due to its good effect in small target segmentation and its scalable structure. In this paper, an improved model based on U-net, namely Atrous Attention U-net (AAU-net), is proposed, in which the Atrous convolution module and attention gate are added. Compared with the ordinary convolution module, the Atrous convolution module expands the receptive field and improves the correlation between objects. Before splicing the corresponding features in encoder and decoder, an integrated attention gate (AGs) is added, which can highlight the significant features transferred by skipping the connection. A series of experiments on the public DRIVE dataset show that the performance of this method is improved compared with the traditional U-shaped network, and the structure is relatively simple compared with other improved methods.

关键词： Training Image segmentation Correlation Convolution Splicing Logic gates Blood vessels

来源：评论

学校读者我要写书评

暂无评论

The Development of Green Olympic Games: A Comparison of CO2Emission Reduction Strategies between PyeongChang 2018 and Beijing 2022 9th

The Development of Green Olympic Games: A Comparison of CO2E...

引用

9th International Conference on Information Technology and Quantitative Management, ITQM 2022

作者： Ding, Xuesong Jiang, Yilin Yang, Banban Su, Jingchun Chen, Liming Li, Na School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China Chinese Academy of Fiscal Sciences Ministry of Finance Beijing100142 China Division of Sports Science and Physical Education Tsinghua University Beijing100084 China Division of Sports Science and Physical Education Tangshan Polytechnic College Tangshan063299 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy Sciences Beijing100190 China

The Olympic Games are striking a balance between economic and ecological benefits. Taking the 5 ice event venues of the 2018 PyeongChang Winter Olympic Games as the research object, the CO2 emissions under the 2018 PyeongChang Low-carbon scenario and 2022 Beijing Low-carbon scenario are compared. The empirical results show that, in terms of venue operation, the Beijing strategies can reduce CO2 emissions by 715.7 t compared with the PyeongChang strategies. In terms of the refrigerant escape, Beijing's adoption of CO2 refrigerant can reduce the emission of CO2 by 1202.2 t compared with the R404 refrigerant used in PyeongChang. This paper confirms the progress of the Green Winter Olympic Games, and may provide implications for the future host countries as well as the cities which in the green transformation. © 2022 The Author(s).

关键词： Refrigerants

来源：评论

学校读者我要写书评

暂无评论

Research on the Rules of Scientists’ knowledge Sharing based on Interdisciplinary Measurement

引用

Procedia Computer Science 2022年 199卷 657-664页

作者： Yong Shi Yunong Wang School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China College of Information Science and Technology University of Nebraska at Omaha NE 68182 USA

With the development of modern science, the adjustment of knowledge structure and the deepening of knowledge, the mode of single discipline research has been gradually broken, and interdisciplinary research has become a necessary way. All the information science and library science articles collected in the core collection of web of science from 1982 to 2020 are used for research and analysis. Through the research of interdisciplinary measurement index, this paper improves the existing interdisciplinary measurement index, uses Excel, Python and other tools to carry out data mining, cleaning, processing, analysis, and determines the interdisciplinary literature data defined in this paper. Finally, with vosviewer and other visual tools, this paper uses the citation network of bibliometrics, keywords co-occurrence and other ways to summarize interdisciplinary science’s law of knowledge sharing and provides suggestions and directions for future research.

关键词： Interdisciplinarity Disciplinary Similarity knowledge Sharing

来源：评论

学校读者我要写书评

暂无评论

Liquidity Commonality Effect in Stock Market and Risk Correlation from the Perspective of Complex Network

引用

Procedia Computer Science 2022年 199卷 725-732页

作者： Haoyuan Feng Jie Wu Kun Guo School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China Academy of Mathematics and Systems Sciences Chinese Academy of Sciences Beijing 100190 China

This paper uses a complex network method to study the liquidity changes and liquidity commonality effects of the Chinese stock market in the two crises of 2015 and 2020. Liquidity indicator and liquidity commonality indicator-the average weighted degree are calculated to revel the risk characteristic of the two crisis. By comparing the two crisis, main conclusions are obtained: Highly leveraged transactions and excess macro-liquidity may lead to the good liquidity condition and the stronger commonality effect in 2015; Besides, the average weighted degree better reflects the systemic risks in a way of revealing the liquidity risk faced by the system.

关键词： Liquidity liquidity commonality systemic risk stock market

来源：评论

学校读者我要写书评

暂无评论

ViGT: Proposal-free Video Grounding with Learnable Token in Transformer

arXiv

引用

arXiv 2023年

作者： Li, Kun Guo, Dan Wang, Meng School of Computer Science and Information Engineering Hefei University of Technology Hefei230601 China Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei230601 China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei230601 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230088 China

The video grounding (VG) task aims to locate the queried action or event in an untrimmed video based on rich linguistic descriptions. Existing proposal-free methods are trapped in complex interaction between video and query, overemphasizing cross-modal feature fusion and feature correlation for VG. In this paper, we propose a novel boundary regression paradigm that performs regression token learning in a transformer. Particularly, we present a simple but effective proposal-free framework, namely Video Grounding Transformer (ViGT), which predicts the temporal boundary using a learnable regression token rather than multi-modal or cross-modal features. In ViGT, the benefits of a learnable token are manifested as follows. (1) The token is unrelated to the video or the query and avoids data bias toward the original video and query. (2) The token simultaneously performs global context aggregation from video and query features. First, we employed a sharing feature encoder to project both video and query into a joint feature space before performing cross-modal co-attention (i.e., video-to-query attention and query-to-video attention) to highlight discriminative features in each modality. Furthermore, we concatenated a learnable regression token [REG] with the video and query features as the input of a vision-language transformer. Finally, we utilized the token [REG] to predict the target moment and visual features to constrain the foreground and background probabilities at each timestamp. The proposed ViGT performed well on three public datasets: ANet Captions, TACoS and YouCookII. Extensive ablation studies and qualitative analysis further validated the interpretability of ViGT. Copyright © 2023, The Authors. All rights reserved.

关键词： Regression analysis

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：