检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

60,566 篇 会议
2,752 篇 期刊文献
1,001 册 图书
12 篇 学位论文
1 件 标准
1 篇 专利
1 篇 科技报告

馆藏范围

64,333 篇 电子文献
2 种 纸本馆藏

日期分布

学科分类号

32,743 篇 工学
- 26,935 篇 计算机科学与技术...
- 15,228 篇 软件工程
- 11,115 篇 信息与通信工程
- 5,608 篇 电气工程
- 3,650 篇 控制科学与工程
- 2,803 篇 电子科学与技术（可...
- 1,191 篇 动力工程及工程热...
- 1,064 篇 机械工程
- 896 篇 仪器科学与技术
- 874 篇 生物工程
- 669 篇 生物医学工程（可授...
- 493 篇 安全科学与工程
- 472 篇 光学工程
- 465 篇 交通运输工程
- 454 篇 网络空间安全
- 425 篇 建筑学
- 324 篇 材料科学与工程（可...
- 324 篇 土木工程
8,463 篇 理学
- 5,964 篇 数学
- 1,473 篇 统计学（可授理学、...
- 1,183 篇 系统科学
- 1,125 篇 物理学
- 1,039 篇 生物学
5,403 篇 管理学
- 3,938 篇 管理科学与工程(可...
- 1,967 篇 工商管理
- 1,711 篇 图书情报与档案管...
781 篇 法学
- 496 篇 社会学
615 篇 医学
- 467 篇 临床医学
- 401 篇 基础医学(可授医学...
576 篇 经济学
- 573 篇 应用经济学
202 篇 文学
187 篇 农学
164 篇 教育学
107 篇 军事学
18 篇 艺术学
2 篇 哲学

主题

7,056 篇 computer network...
4,674 篇 computer archite...
4,373 篇 computer science
4,159 篇 distributed comp...
3,703 篇 wireless sensor ...
2,957 篇 application soft...
2,784 篇 protocols
2,579 篇 computational mo...
2,307 篇 hardware
2,272 篇 neural networks
2,191 篇 bandwidth
2,152 篇 delay
2,141 篇 distributed comp...
2,037 篇 routing
1,852 篇 costs
1,609 篇 resource managem...
1,608 篇 intelligent netw...
1,512 篇 network topology
1,422 篇 control systems
1,402 篇 ip networks

机构

93 篇 school of comput...
66 篇 ibm thomas j. wa...
60 篇 department of co...
59 篇 department of co...
49 篇 school of comput...
45 篇 school of electr...
36 篇 school of comput...
36 篇 department of sy...
32 篇 college of compu...
32 篇 department of el...
29 篇 inria
29 篇 school of comput...
29 篇 department of el...
28 篇 department of el...
28 篇 ibm thomas j. wa...
28 篇 department of co...
27 篇 department of el...
27 篇 department of sy...
27 篇 department of co...
27 篇 shandong provinc...

作者

50 篇 m. takizawa
26 篇 kowalski dariusz...
26 篇 li li
25 篇 santoro nicola
24 篇 yu wang
24 篇 s.k. das
23 篇 k.g. shin
23 篇 kuhn fabian
23 篇 peleg david
23 篇 p.k. srimani
23 篇 jun wang
23 篇 klaus wehrle
23 篇 duato j.
22 篇 dhabaleswar k. p...
22 篇 l.m. ni
21 篇 sens pierre
21 篇 xiaodong lu
19 篇 guohong cao
19 篇 y. shibata
18 篇 torsten hoefler

语言

62,965 篇 英文
921 篇 其他
417 篇 中文
49 篇 葡萄牙文
7 篇 法文
4 篇 西班牙文
3 篇 德文
3 篇 日文
3 篇 俄文

检索条件"任意字段=International Symposium on Computer Networks and Distributed Systems"

共 64335 条记录，以下是1081-1090 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

PROGRESS TOWARD TOTAL CIH FOR PHOTOMASK SHOPS 8

PROGRESS TOWARD TOTAL CIH FOR PHOTOMASK SHOPS

引用

8th Annual BACUS symposium on Microlithography

作者： Austin, Norman A. AB Networks Inc. United States

AB networks, Inc. is automating the photomask industry by introducing CIM (computer Integrated Manufacturing) technology in the areas of network communication, production control, process and inspection data collectio... 详细信息

ISBN: (纸本)9781510668805

关键词： Photomasks

来源：评论

学校读者我要写书评

暂无评论

Integration of Heterogeneous IDS with SIEM for DDoS Attack Detection in computer Networked Multi-Organizational Environments 5

Integration of Heterogeneous IDS with SIEM for DDoS Attack D...

引用

5th IEEE international Conference on Communications, Information, Electronic and Energy systems, CIEES 2024

作者： Maliki, M. Akmal Sukarno, Parman Wardana, Aulia Arif Telkom University School of Computing Bandung Indonesia Wroclaw University of Science and Technology Faculty of ICT Wroclaw Poland

ISBN: (纸本)9798350352863

The increasing reliance on computer networks for business operations has led to a rise in distributed Denial of Service (DDoS) attacks. These attacks pose significant threats to network security, economic stability, and organizational operations. Organizations connected through the same network are particularly vulnerable. In response to these growing threats, detection systems have been developed to integrate heterogeneous Intrusion Detection systems (IDS) with Security Information and Event Management (SIEM) systems. This integration assists in the detection of DDoS attacks within multi-organizational environments. The system employs the Opensearch dashboard, providing a centralized and efficient interface for the Security Operations Center. System testing was conducted through coordinated DDoS attack simulations by three attackers over a duration of 7-8 minutes. The Snort IDS demonstrated an average detection rate of 95.4%, with an alert correlation mechanism efficiency of 84.6%. Among the IDS systems tested, Zeek IDS consumed the most resources, with an average CPU usage of 24.6% and memory usage of 86.5%. In contrast, the Wazuh Dashboard exhibited lower resource consumption, with an average CPU usage of 0.6% and memory usage of 5.2%. © 2024 IEEE.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

A distributed Technique of Optimization Problems Solving Based on Efficient Workload Assignment 27th

A Distributed Technique of Optimization Problems Solving Ba...

引用

27th international Conference on distributed computer and Communication networks, DCCN 2024

作者： Klimenko, Anna Institute of IT and Security Technologies Russian State University for Humanities Moscow Russia

ISBN: (纸本)9783031808524

Currently, the efficiency improvement of complex technical systems is an urgent scientific task, which in numerous cases is formalized via optimization problem and solved by some well-known optimization methods. Metaheuristics are used intensively in this field due to their possibility to generate acceptable solutions in restricted time periods. However, it is known that with the decrease of performing time the solution accuracy of metaheuristics degrades, as well as algorithm’s convergence depends on its exploitation/exploration features and preliminary set parameters. Parallel metaheuristics implementations are used to improve algorithms performance. In this paper a distributed technique of computationally-hard optimization problems solving based on efficient workload assignment is presented and described. The novelty of the technique proposed is that the additional procedure of metaheuristics instances forming and distribution is added, which creates metaheuristic instances of a various computational complexity and assigns them to the most suited computing resources to perform parallel independent runs within the operation time restriction. The workload generated by metaheuristics blocks is distributed efficiently by means of metaheuristics portfolio usage. The latter makes it possible to improve the metaheuristics instances distribution and computational complexities forming so as to put the largest metaheuristic block to the node with the highest performance with the iterative improvement of the distribution, considering the full set of computing resources constraints and criteria. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

An Experimental Setup for Robot Learning from Human Observation using Deep Neural networks

An Experimental Setup for Robot Learning from Human Observat...

引用

2023 international symposium on Signals, Circuits and systems, ISSCS 2023

作者： Elachkar, Michael Mozaffari, Saeed Ahmadi, Majid Ahamed, Jalal Alirezaee, Shahpour University of Windsor Electrical and Computer Engineering Department Windsor Canada University of Windsor Mechanical Automotive and Material Engineering Department Windsor Canada

ISBN: (纸本)9798350342031

Industrial robots have gained great popularity in the last twenty years and become an integral component in many sectors empowering automation. Typically, trained technicians program robots before being commissioned into a production environment to perform a specific job. However, this method is suitable when the working environment is well structured with fixed parameters. Learning from demonstration (LfD) has emerged as an alternative robot programming paradigm for working in a dynamic production atmosphere with several uncertainties to obviate re-programming robots when something changes in the workplace. In this paper, we developed an LfD system based on computer vision to observe human actions and deep learning to perceive the demonstrator's actions and manipulated objects. Object detection, object classification, pose estimation, and action recognition tasks are performed by deep neural networks. The proposed LfD method was demonstrated and tested with industrial robots for a pick-and-place application with 95% accuracy. © 2023 IEEE.

关键词： Industrial robots

来源：评论

学校读者我要写书评

暂无评论

Multi-Scale Sampling Based MLP networks for Anomaly Detection in Multivariate Time Series 29

Multi-Scale Sampling Based MLP Networks for Anomaly Detectio...

引用

29th IEEE international Conference on Parallel and distributed systems, ICPADS 2023

作者： Li, Haojie Xu, Hongzuo Peng, Wei Shen, Chiran Qiu, Xianwen National University of Defense Technology College of Computer Changsha China

ISBN: (纸本)9798350330717

Multivariate time series data are produced in various domains, including AIOps, space crafts, and healthcare. Identifying anomalies within them is significant to ensure the stability of target systems. Current anomaly detectors mainly focus on devising intricate network structures based on recurrent neural networks, Transformers, or graph neural networks to model the temporal and inter-variate dependencies of the input time series. Nevertheless, complex models often lead to computational burden in training and inferencing stage. Also, system operators have to understand the technical details of these complex models to fine-tune them or add new modules for different needs. This motivates us to consider an intriguing question: can we construct an anomaly detection model merely based on simple networks? In this paper, we propose FlightAD, a light but effective anomaly detection model using only multi-layer perceptron (MLP) networks. FlightAD applies MLP networks on top of a multi-scale sampling strategy, followed by an informationfusing mechanism to fuse the learned features. More specific, the multi-scale sampling strategy is used to extract abundant temporal patterns of time series, and the MLP blocks applied to it can simultaneously model the dependencies along the time axis and dependencies between different sampled sub-sequences (i.e., different variables). Finally, we wield an informationfusing module to fully integrate the learned multi-scale features. Extensive experiments on six real-world datasets show that our model outperforms seven state-of-the-art competitors on average by 2.1%-18.2% in F1 score and 3.8%-38.9% in AUC-PR. © 2023 IEEE.

关键词： anomaly detection multi-layer perceptrons multivariate time series

来源：评论

学校读者我要写书评

暂无评论

FedRAL: Cost-Effective distributed Annotation via Federated Reinforced Active Learning

FedRAL: Cost-Effective Distributed Annotation via Federated ...

引用

2024 IEEE international Conference on Big Data, BigData 2024

作者： Lazaridis, Yannis Kastellos, Anestis Psaltis, Athanasios Daras, Petros Centre for Research and Technology Hellas Thessaloniki Greece

ISBN: (纸本)9798350362480

This paper addresses the challenge of reducing annotation costs in distributed learning environments, particularly in systems with limited data and computational resources, such as those found in edge devices. We propose Federated Reinforced Active Learning, a framework that integrates Federated Learning with Reinforced Active Learning to optimize data labeling under strict cost constraints. The method is designed for small-scale networks where data is sparse, and minimal training epochs are available. By utilizing reinforcement learning within active learning, the system selects the most informative data samples, allowing for efficient training while significantly reducing the need for extensive annotations. This approach is particularly suited for environments where minimizing both annotation and computational costs is critical, such as in applications where cost efficiency and resource limitations are top priorities. The proposed method is evaluated on the CIFAR-10 and CIFAR-100 datasets using ResNet18, across 5 and 10 clients. Results demonstrate that the method significantly reduces annotation costs and improves learning outcomes, making it an ideal solution for cost-sensitive distributed systems. © 2024 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Cloud-Enabled Neural networks for Intelligent Vehicle Emissions Tracking and Analysis

Cloud-Enabled Neural Networks for Intelligent Vehicle Emissi...

引用

2024 IEEE international Conference on Automation and Computation, AUTOCOM 2024

作者： Anusha, N. Jeslin, J Gnana Srividhya, V. Gupta, Nukala Sujata Meenakshi, R. Srinivasan, C. Vellore Institute of Technology School of Computer Science and Engineering Department of IoT Tamil Nadu Vellore India Rmk College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Meenakshi College of Engineering Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Chaitanya Bharathi Institute of Technology Department of Computer Engineering and Technology Hyderabad Gandipet India Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350382723

A system for smart vehicle emissions monitoring and analysis using cloud computing and neural networks is presented in this paper. As global environmental concerns develop, monitoring and reducing vehicle emissions is crucial. Scalability and real-time data processing are issues for traditional approaches. Thus, cloud-enabled neural network architecture for scalable and efficient vehicle emissions monitoring using distributed computing is developed. A neural network model trained on various vehicle emission datasets, allowing for precise pattern analysis and prediction of emissions. The scalability of the system is guaranteed by using cloud resources, which can accommodate the rising amount of data created by an increasing number of vehicles. By incorporating cloud-based data processing seamlessly, real-time monitoring is accomplished, enabling immediate analysis and prompt emission alerts. The suggested emissions tracking platform is robust and scalable to intelligent transportation systems by revealing vehicle emissions' environmental effect. Future smart city and sustainable urban transportation developments are built on cloud computing and neural networks. The proposed system shows how cloud-enabled neural networks may solve complicated vehicle emissions problems. © 2024 IEEE.

关键词： Scalability

来源：评论

学校读者我要写书评

暂无评论

Federated Multi-Agent Reinforcement Learning for AoI Minimization in UAV-Enabled IoV-MEC systems 22

Federated Multi-Agent Reinforcement Learning for AoI Minimiz...

引用

22nd IEEE international symposium on Parallel and distributed Processing with Applications, ISPA 2024

作者： Xu, Shoukun Zhang, Yu Wang, Xueyuan Gursoy, M. Cenk Changzhou University Academy of Computer Science and Artificial Intelligence Changzhou China Syracuse University Department of Electrical Engineering and Computer Science SyracuseNY13244 United States

ISBN: (纸本)9798331509712

With the advancement of Mobile Edge Computing (MEC), effective solutions for communication scenarios, including the industrial Internet of Things (IoT) and the Internet of Vehicles (IoV), are becoming increasingly feasible. Unmanned aerial vehicles (UAVs) can further enhance flexibility in delivering computational services within MEC contexts. Addressing the urgent need for information freshness, we propose a three-tier IoV-MEC system, supported by multiple UAVs and a cloud center, aiming to minimize the system's average age of information (AoI). We propose a heterogeneous multi-agent reinforcement learning algorithm based on the actor-critic framework, where vehicles act as data sources, UAVs serve as edge devices, and the cloud acts as a control center. All three tiers learn interaction strategies cooperatively based on the observations. To further enhance system performance, we implement an efficient federated learning method, allowing same-tier agents to share learning parameters, thus improving system performance and convergence speed. Extensive simulation results demonstrate that the proposed algorithm outperforms baseline algorithms in terms of average AoI and convergence speed. © 2024 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

A Base Algorithm for Intelligent Traffic Management System for Urban Transportation using 6G Network 18

A Base Algorithm for Intelligent Traffic Management System f...

引用

18th IEEE international Conference on Advanced networks and Telecommunications systems, ANTS 2024

作者： Salam, Sameera M. Mitra, Abhinivesh Bits Pilani Hyderabad Campus Dept. of Computer Science and Information Systems Secunderabad India

ISBN: (纸本)9798350391725

Efficient traffic management in urban environments is essential for minimizing congestion and ensuring smooth transportation flow. 6G network is expected to offer faster data speeds, lower latency, and enhanced connectivity. Traditional approaches often struggle to adapt to dynamic traffic patterns and overlook the influence of geographical factors on traffic flow. To address these challenges, this study proposes an innovative approach that integrates gravitational modeling and cluster detection techniques to optimize route planning and congestion management in transportation networks. The shorter response time of the algorithm makes it well-suited for traffic management in a 6G network. This capability allows for real-time data processing and immediate adjustments, enhancing overall traffic flow. The proposed approach utilizes gravitational modeling to simulate traffic interactions between road segments or intersections within the transportation network. By considering factors such as traffic density, user influence, and geographical proximity, the approach aims to identify clusters of interconnected road segments or intersections with similar traffic patterns. These clusters serve as strategic focal points for developing targeted route planning and congestion management strategies. © 2024 IEEE.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

The Smart Optimization of Security systems in Wireless Personal Sensor networks 2

The Smart Optimization of Security Systems in Wireless Perso...

引用

2nd IEEE international Conference on distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Das, Sunanda Sindhu Madhuri, G. Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350347456

Wireless personal sensor networks (WPSNs) are an emerging technology that provides a platform for monitoring and collecting data from a variety of sources. These networks are used to monitor environmental, health, and even lifestyle factors. As the use of WPSNs continues to grow, it is important to consider the security implications of using these networks. WPSNs rely on a variety of technologies to ensure secure communication between devices. These include encryption, authentication, secure protocols, and secure key management. Encryption is used to protect data from being intercepted and decoded by an unauthorized user. Authentication is used to verify the personality of the user and the device attempting to access the WPSN. Secure protocols are used to ensure secure communication between the devices and the server. Finally, secure key management is used to manage and store the encryption keys used to protect the data. In addition to encryption, authentication, and secure protocols, WPSNs must also be designed with a robust access control system. Access control systems are used to limit access to the WPSN based on user credentials and other factors. This assist ensure that authorized users alone can access the data stored on the WPSN. © 2023 IEEE.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共500页 << < 105 106 107 108 109 110 111 112 113 114 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：