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

6,705 篇 会议
116 册 图书
70 篇 期刊文献

馆藏范围

6,891 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

3,560 篇 工学
- 3,366 篇 计算机科学与技术...
- 1,736 篇 软件工程
- 1,054 篇 信息与通信工程
- 673 篇 电气工程
- 228 篇 控制科学与工程
- 179 篇 电子科学与技术（可...
- 143 篇 机械工程
- 97 篇 动力工程及工程热...
- 97 篇 生物工程
- 94 篇 测绘科学与技术
- 42 篇 生物医学工程（可授...
- 40 篇 仪器科学与技术
- 39 篇 光学工程
- 34 篇 建筑学
- 29 篇 土木工程
- 28 篇 网络空间安全
- 27 篇 安全科学与工程
771 篇 理学
- 568 篇 数学
- 112 篇 生物学
- 102 篇 统计学（可授理学、...
- 100 篇 物理学
- 75 篇 系统科学
- 37 篇 化学
511 篇 管理学
- 383 篇 管理科学与工程(可...
- 197 篇 工商管理
- 155 篇 图书情报与档案管...
82 篇 医学
- 80 篇 临床医学
- 25 篇 基础医学(可授医学...
42 篇 经济学
- 42 篇 应用经济学
35 篇 法学
- 25 篇 社会学
12 篇 农学
10 篇 文学
8 篇 教育学
8 篇 军事学
1 篇 艺术学

主题

898 篇 distributed comp...
802 篇 computer network...
513 篇 concurrent compu...
450 篇 wireless sensor ...
377 篇 parallel process...
354 篇 computer science
352 篇 routing
344 篇 neural networks
341 篇 computational mo...
304 篇 computer archite...
260 篇 application soft...
255 篇 network topology
253 篇 peer to peer com...
253 篇 protocols
244 篇 bandwidth
235 篇 grid computing
232 篇 software enginee...
189 篇 costs
177 篇 intelligent netw...
176 篇 artificial intel...

机构

28 篇 institute of com...
24 篇 shandong provinc...
20 篇 key laboratory o...
15 篇 shandong fundame...
14 篇 department of co...
13 篇 university of ch...
12 篇 department of co...
11 篇 department of co...
11 篇 department of co...
11 篇 institute of com...
11 篇 national laborat...
11 篇 beijing universi...
10 篇 college of compu...
10 篇 institute of inf...
10 篇 school of cyber ...
10 篇 department of co...
10 篇 school of comput...
9 篇 shandong enginee...
9 篇 department of co...
9 篇 school of comput...

作者

16 篇 jiannong cao
15 篇 m. takizawa
15 篇 li dongsheng
15 篇 shen hong
15 篇 hong shen
14 篇 shietung peng
14 篇 eyas el-qawasmeh
13 篇 lemin li
13 篇 rothermel kurt
12 篇 hai jin
11 篇 dongsheng li
11 篇 wei zhang
10 篇 koibuchi michihi...
10 篇 jack dongarra
10 篇 t. enokido
10 篇 wang yang
10 篇 stephen l. scott
10 篇 j. duato
10 篇 m. ould-khaoua
9 篇 duerr frank

语言

6,711 篇 英文
168 篇 其他
17 篇 中文

检索条件"任意字段=IASTED International Conference on Parallel and Distributed Computing and Networks"

共 6891 条记录，以下是791-800 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：

Learning Dynamic Behavior Patterns for Fraud Detection

Learning Dynamic Behavior Patterns for Fraud Detection

引用

IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Zijun Huang Junhang Wu Lingfei Ren Ruimin Hu Dengshi Li National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Wuhan China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University Wuhan China School of Cyber Engineering Xidian University Xi'an China School of Artificial Intelligence Jianghan University Wuhan China

Telecom fraud detection is considered a needle in a haystack task due to the fact that fraudsters are usually hidden among a large number of normal users. In fact, a fraudster will usually act in a continuous manner over a period of time to achieve fraudulent purposes. At the same time, fraudsters are constantly looking for new fraudulent targets. Therefore, we consider a behavioral pattern-based fraudster identification system called HADyn-LSTM for telecommunication network fraud detection. Motivated by the breakthroughs in deep learning (DL), we make an effort to judge whether a user is a fraudster is based on the user's behavior sequence in the social network, which means that we study the difference between normal users and fraudsters through dynamic behavior patterns rather than static statistical attributes. Particularly, Based on sequential neural networks and attention mechanisms, we design an end-to-end system that learns and extracts the dynamic patterns of user behavior sequences. Furthermore, We tested our system on three datasets of different sizes. The test results show that the HADyn-LSTM system performs better than the static attribute-based method.

关键词： Social networking (online) Neural networks Telephone sets Behavioral sciences Fraud Telecommunications Safety

来源：评论

学校读者我要写书评

暂无评论

NFT-basedAccess Control in Named Data networks

NFT-basedAccess Control in Named Data Networks

引用

IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Hui Zhao Xiaodong Zhang Ru Li College of Computer Science Inner Mongolia University Hohhot China

The information cache technology in the Named Data Network (NDN) decouples the location of the Content Provider (CP) from the data, which leads to the data in the storage nodes facing security threats due to the lack of security control. Therefore, access control becomes extremely important. Because Ciphertext-Policy Attribute-Based Encryption (CP-ABE) supports sending data to a group of unknown recipients and realizes flexible and fine-grained access control, CP-ABE is often used in the access control of NDN. However, there are two problems when CP-ABE is directly applied to NDN: first, CP is required to be online all the time to verify the legitimacy of users and distribute decryption keys; Second, illegal users can obtain ciphertext. In view of the above problems, we propose an access control scheme based on Non-Fungible Token(NFT). Smart contracts distribute AttributeNFT and AccessNFT for users, and provide credentials for users to obtain keys and ciphertext. NDN routers only forward ciphertext data packets to valid users by implementing the filtering mechanism based on AccessNFT, and finally achieve the purpose of protecting data and achieving the safe distribution of data. Finally, we implement the system prototype on the Hyperledger Fabric and analyze the performance of the smart contract with the caliper. The experimental results show that the access delay of the smart contract is low and can meet the requirements of access control.

关键词： Access control Filtering distributed ledger Smart contracts Prototypes Fabrics Encryption

来源：评论

学校读者我要写书评

暂无评论

A Ransomware Classification Method Based on Entropy Map

A Ransomware Classification Method Based on Entropy Map

引用

IEEE international Symposium on parallel and distributed Processing with Applications and IEEE international conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： XiZhen Deng M. Jiang MingCan Cen College of Electronics and Engineering Guangxi Normal University China

With the rapid development and popularization of internet technologies such as AI and 5G, more and more organizations and individuals have suffered a dramatic increase in the number of ransomware attacks, which has brought substantial economic losses to them. Ransomware is an illegal act that blackmails victims into paying a ransom by locking their devices or encrypting files. Achieving fast and effective ransomware classification, attack intent and pattern analysis can improve the efficiency of security analysts and discover ransomware variants earlier. Therefore, we propose a new ransomware classification method, which uses the entropy map extracted from the ransomware binary file for classification. The entropy map retains more fine-grained features in the ransomware family, which can improve the classification result. Aiming at the problem of data imbalance among ransomware families, we propose a data augmentation method based on the Cycle-GAN network, which combines the fine-tuning technology in transfer learning to improve the classification result of the framework further. At the same time, the attention mechanism is introduced into VGG-16. It is used to enhance the ability of feature extraction of the network. The experimental results show that the proposed method achieves the best performance on 14 ransomware families, and the accuracy rate can reach 97.16%, which is better than other traditional ransomware visualization classification methods. Our proposed method still has the best classification performance compared with other neural networks.

关键词： Visualization Transfer learning Neural networks Organizations Network security Feature extraction Ubiquitous computing

来源：评论

学校读者我要写书评

暂无评论

An Artificial Intelligence Driven Method for Power System Control Based on the Cloud-Edge Collaboration Architecture

An Artificial Intelligence Driven Method for Power System Co...

引用

Digital Twins and parallel Intelligence (DTPI), IEEE international conference on

作者： Wenchen Li Yanhao Huang Chunjiang He Chenglong Xu Peidong Xu Tianlu Gao Jun Zhang China Electric Power Research Institute Beijing China School of Electrical Engineering and Automation Wuhan University Wuhan China

ISBN: (数字)9781665492270

ISBN: (纸本)9781665492287

The new-type power system with the high penetration of renewable energy accessed is of strong uncertainty and complexity, which can be challenging for the traditional methods to control. It's significant to introduce artificial intelligence to meet the challenge. This paper proposes a cloud-edge collaborative framework based on multi-agent deep reinforcement learning for power system regulation. Using an unsupervised clustering algorithm, the power grid is decomposed into several sub-networks according to the geographical relationship. Then, edge computing platforms are set up on each sub-network, where agents are deployed. The distributed control problem of each subnetwork can be modeled as a Markov decision model. The global observation information of the system is delivered to each edge platform through the cloud computing center, and all agents are trained to learn the best regulation strategy according to the global information. The proposed method can effectively decompose the centralized tasks and transfer them to the edge side, alleviating the pressure on the cloud center and enhancing the robustness of system operation.

关键词： Training Deep learning Cloud computing Computational modeling Collaboration Clustering algorithms Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Continuous, Real-Time Object Detection on Mobile Devices without Offloading 40

Continuous, Real-Time Object Detection on Mobile Devices wit...

引用

40th IEEE international conference on distributed computing Systems (ICDCS)

作者： Liu, Miaomiao Ding, Xianzhong Du, Wan Univ Calif Merced Dept Comp Sci & Engn Merced CA 95343 USA

ISBN: (纸本)9781728170022

This paper presents AdaVP, a continuous and real-time video processing system for mobile devices without offloading. AdaVP uses Deep Neural Network (DNN) based tools like YOLOv3 for object detection. Since DNN computation is time-consuming, multiple frames may be captured by the camera during the processing of one frame. To support real-time video processing, we develop a mobile parallel detection and tracking (MPDT) pipeline that executes object detection and tracking in parallel. When the object detector is processing a new frame, a light-weight object tracker is used to track the objects in the accumulated frames. As the tracking accuracy decreases gradually, due to the accumulation of tracking error and the appearance of new objects, new object detection results are used to calibrate the tracking accuracy periodically. In addition, a large DNN model produces high accuracy, but requires long processing latency, resulting in a great degradation for tracking accuracy. Based on our experiments, we find that the tracking accuracy degradation is also related to the variation of video content, e.g., for a dynamically changing video, the tracking accuracy degrades fast. A model adaptation algorithm is thus developed to adapt the DNN models according to the change rate of video content. We implement AdaVP on Jetson TX2 and conduct a variety of experiments on a large video dataset. The experiment results reveal that AdaVP improves the accuracy of the state-of-the-art solution by up to 43.9%.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

distributed macroscopic traffic simulation with Open Traffic Models 23

Distributed macroscopic traffic simulation with Open Traffic...

引用

23rd IEEE international conference on Intelligent Transportation Systems (ITSC)

作者： Gomes, Gabriel Ugirumurera, Juliette Li, Xiaoye S. Univ Calif Berkeley Inst Transportat Studies Berkeley CA 94720 USA Natl Renewable Energy Lab Computat Sci Ctr Denver CO USA Lawrence Berkeley Natl Lab Computat Res Div Berkeley CA USA

ISBN: (纸本)9781728141497

This paper presents OTM-MPI, an extension of the Open Traffic Models platform (OTM) for running macroscopic traffic simulations in high-performance computing environments. OTM-MPI represents the first open-source, distributed-memory, macroscopic simulation model developed for modern high performance parallel machines and large networks. Macroscopic simulations are appropriate for studying regional traffic scenarios when aggregate trends are of interest, rather than individual vehicle traces. They are also appropriate for studying the routing behavior of classes of vehicles, such as app-informed vehicles. The network partitioning was performed with METIS. Inter-process communication was done with MPI (message-passing interface). Results are provided for two networks: one realistic network which was obtained from Open Street Maps for Chattanooga, TN, and another larger synthetic grid network. The software recorded a speedups of 198x using 256 cores for Chattanooga, and 475x with 1,024 cores for the synthetic network.

关键词： Traffic simulation parallel simulation Macroscopic traffic simulation parallel computing

来源：评论

学校读者我要写书评

暂无评论

distributed Novelty Detection at the Edge for IoT Network Security 21st

Distributed Novelty Detection at the Edge for IoT Network Se...

引用

21st international conference on Computational Science and Its Applications (ICCSA)

作者： Puhl, Luis Cassales, Guilherme Weigert Guardia, Helio Crestana Senger, Hermes Univ Fed Sao Carlos Sao Carlos Brazil

ISBN: (纸本)9783030869700;9783030869694

The ongoing implementation of the Internet of Things (IoT) is sharply increasing the number and variety of small devices on edge networks. Likewise, the attack opportunities for hostile agents also increases, requiring more effort from network administrators and strategies to detect and react to those threats. For a network security system to operate in the context of edge and IoT, it has to comply with processing, storage, and energy requirements alongside traditional requirements for stream and network analysis like accuracy and scalability. Using a previously defined architecture (IDSA-IoT), we address the construction and evaluation of a support mechanism for distributed Network Intrusion Detection Systems based on the MINAS Data Stream Novelty Detection algorithm. We discuss the algorithm steps, how it can be deployed in a distributed environment, the impacts on the accuracy and evaluate performance and scalability using a cluster of constrained devices commonly found in IoT scenarios. The obtained results show a negligible accuracy loss in the distributed version but also a small reduction in the execution time using low profile devices. Although not efficient, the parallel version showed to be viable as the proposed granularity provides equivalent accuracy and viable response times.

关键词： Novelty detection Intrusion detection Data streams distributed system Edge computing Internet of Things

来源：评论

学校读者我要写书评

暂无评论

DeepHop on Edge: Hop-by-hop Routing by distributed Learning with Semantic Attention 20

DeepHop on Edge: Hop-by-hop Routing by Distributed Learning ...

引用

49th international conference on parallel Processing (ICPP)

作者： He, Bo Wang, Jingyu Qi, Qi Sun, Haifeng Zhuang, Zirui Liu, Cong Liao, Jianxin Beijing Univ Posts & Telecommun Beijing Peoples R China China Mobile Res Inst Beijing Peoples R China

ISBN: (纸本)9781450388160

Multi-access Edge computing (MEC) and ubiquitous smart devices help serve end-users efficiently and optimally through providing emerging edge-deployed services. Meanwhile, heavy and time-varying traffic loads are produced in the edge network, so that an efficient traffic forwarding mechanism is required. In this paper, we propose a parallel and distributed learning approach, DeepHop, to adapt to the volatile environments and realize hop-by-hop routing. The Multi-Agent Deep Reinforcement Learning (MADRL) is used to alleviate the edge network congestion and maximize the utilization of network resources. DeepHop determines the routing among edge network nodes for heterogeneous types of traffic according to the current workload and capability. By joining with an attention mechanism, DeepHop obtains the semantics from the elements of the network state to help the agents learn the importance of each element on routing. Experiment results show that DeepHop achieves the increase of successfully transmitted packets by 15% compared with the state-of-the-art algorithms. Besides, DeepHop with an attention mechanism reduces convergence time by nearly half compared with the common-used structures of neural networks.

关键词： distributed routing wireless edge networks multi-agent reinforcement learning self-attention

来源：评论

学校读者我要写书评

暂无评论

A Dual-stage Attention Based SDN Traffic Prediction Method

A Dual-stage Attention Based SDN Traffic Prediction Method

引用

IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Chenjing Gao Junli Wang Chungang Yan Key Laboratory of Embedded System and Service Computing (Tongji University) Ministry of Education National (Province-Ministry Joint) Collaborative Innovation Center for Financial Network Security Tongji University Shanghai China

Traffic matrix is the main research object of traffic prediction in software-defined networking. Accurate and timely traffic matrix prediction plays an important role in avoiding network congestion. While various methods have been proposed in previous studies to solve the SDN traffic prediction problem, few of them consider both inter- and intra-flow features. In this paper, we propose a dual-stage attention based Traffic Prediction method for the SDN traffic matrix prediction task. First, our method uses temporal pattern attention as the inter-flow attention mechanism before the encoding stage to realize adaptive feature extraction. Then, temporal attention is introduced as the intra-flow attention mechanism before the decoding stage to capture long-term temporal dependencies. Finally, we use the autoregressive module to handle the highly dynamic SDN traffic volume. Experimental results show that our proposed SDN traffic prediction method can capture more traffic features and improve the SDN traffic matrix prediction performance to some extent.

关键词： Network topology Time series analysis Prediction methods Machine learning Feature extraction Graph neural networks Encoding

来源：评论

学校读者我要写书评

暂无评论

Towards Efficient Elastic parallelism for Deep Learning Processor

Towards Efficient Elastic Parallelism for Deep Learning Proc...

引用

IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Jinyu Cheng Ruyi Qian Qinwen Shi Gaomei Hu Mengjuan Gao Qirun Huo Yuanchao Xu College of Information Engineering Capital Normal University Beijing China SKL of Computer Architecture CAS Institute of Computing Technology Beijing China

Resources underutilization is the most troublesome problem faced by almost all deep learning processors. To address this challenge, researchers have proposed various methods, especially in exploiting the parallelism of deep neural network models. However, some parallelisms have mutual effects, for example, intra-operator parallelism has adverse effects on inter-operator parallelism, resulting in a waste of resources. In order to make full use of chip resources, this paper applies the idea of elastic scheduling to the driver level of deep learning processor to achieve elastic parallelism. That is, if a task consists of multiple independent subtasks, it can be executed as long as the minimum resource requirements of the sub tasks are met. In addition, based on greedy scheduling algorithm, some improved methods are proposed, including subtask awareness, NUMA awareness, and cluster alignment awareness. Our analysis and preliminary evaluation demonstrate that, by reducing intra-operator parallelism, elastic parallelism can help improve chip utilization, and our proposed scheduling optimizations can also further improve the overall system performance.

关键词： Deep learning Program processors Scheduling algorithms System performance Pipelines Neural networks Optimization methods

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 << < 76 77 78 79 80 81 82 83 84 85 > >>

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：