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

10,918 篇 会议
230 篇 期刊文献
173 册 图书
3 篇 学位论文

馆藏范围

11,324 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

6,681 篇 工学
- 6,110 篇 计算机科学与技术...
- 2,915 篇 软件工程
- 1,181 篇 电气工程
- 1,069 篇 信息与通信工程
- 482 篇 电子科学与技术（可...
- 358 篇 控制科学与工程
- 176 篇 仪器科学与技术
- 152 篇 机械工程
- 117 篇 动力工程及工程热...
- 113 篇 生物医学工程（可授...
- 101 篇 生物工程
- 87 篇 光学工程
- 87 篇 建筑学
- 69 篇 土木工程
- 68 篇 网络空间安全
- 65 篇 化学工程与技术
- 63 篇 材料科学与工程（可...
- 58 篇 安全科学与工程
1,468 篇 理学
- 976 篇 数学
- 311 篇 物理学
- 156 篇 系统科学
- 140 篇 统计学（可授理学、...
- 136 篇 生物学
- 83 篇 化学
898 篇 管理学
- 648 篇 管理科学与工程(可...
- 307 篇 图书情报与档案管...
- 290 篇 工商管理
145 篇 医学
- 120 篇 临床医学
- 62 篇 基础医学(可授医学...
62 篇 经济学
- 62 篇 应用经济学
56 篇 法学
34 篇 农学
26 篇 教育学
18 篇 文学
11 篇 军事学

主题

1,464 篇 parallel process...
584 篇 computer archite...
555 篇 distributed comp...
534 篇 application soft...
531 篇 computational mo...
528 篇 concurrent compu...
342 篇 hardware
319 篇 graphics process...
309 篇 scalability
308 篇 parallel program...
306 篇 graphics process...
304 篇 computer science
285 篇 runtime
263 篇 big data
262 篇 optimization
250 篇 parallel process...
226 篇 throughput
225 篇 processor schedu...
214 篇 resource managem...
209 篇 bandwidth

机构

31 篇 national laborat...
23 篇 science and tech...
21 篇 department of co...
19 篇 national laborat...
18 篇 university of ch...
17 篇 school of comput...
17 篇 institute of com...
16 篇 school of comput...
15 篇 college of compu...
15 篇 georgia inst tec...
15 篇 barcelona superc...
15 篇 intel corporatio...
14 篇 school of comput...
14 篇 chinese acad sci...
14 篇 department of co...
13 篇 tsinghua univ de...
13 篇 ibm thomas j. wa...
13 篇 cent s univ sch ...
13 篇 college of compu...
13 篇 ohio state univ ...

作者

21 篇 jack dongarra
16 篇 badia rosa m.
16 篇 liu jie
15 篇 wang guojun
15 篇 yijie wang
15 篇 a. choudhary
14 篇 anon
14 篇 kurt rothermel
13 篇 jun wang
13 篇 koldehofe boris
13 篇 mencagli gabriel...
13 篇 prodan radu
13 篇 wang yijie
12 篇 fahringer thomas
12 篇 dongsheng li
12 篇 zomaya albert y.
12 篇 navaux philippe ...
12 篇 yong dou
11 篇 fernandes luiz g...
11 篇 guangwen yang

语言

11,155 篇 英文
135 篇 其他
36 篇 中文
2 篇 俄文
2 篇 土耳其文
1 篇 德文

检索条件"任意字段=International Conference on Parallel and Distributed Processing Techniques and Applications"

共 11324 条记录，以下是1241-1250 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：

Real-Time Analytics for Big Data in Smart City applications: Transforming Urban Environments with Data-Driven Insights

Real-Time Analytics for Big Data in Smart City Applications:...

引用

Automation and Computation (AUTOCOM), international conference on

作者： Avinash Khanderi Gnanajeyaraman Rajaram Ramy Riad Hussein Prashant Johri T. Mohanraj M. Balamurugan Walmart Inc. Senior Data Engineer Bentonville Arkansas Department of CSE SIMATS Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq School of Computing Science and Engineering Galgotias University Greater Noida India Department of Computer Science Engineering Karpagam Academy of Higher Education Coimbatore India Department of EEE Excel Engineering College Komarapalayam India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

This paper offers an overview of real-time analytics for smart cities proposing a framework for real-time data processing to improve the urban landscape. In the proposed system, large-scale data-streams can be processed using advanced machine learning algorithms, edge computing, and distributed data storage. Analyzing the outcomes of the evaluation procedure evidences reportable performance enhancements in the areas of smart city applications. Average traffic speed in transportation systems in the same period rose by 60%, concurrency and response to incidents likewise cut down by 40% and 53% respectively. The energy management systems responded with a 16% decrease in maximum energy load and the waste reduction was by 50%, while the costs savings was by 25% increase. Public safety applications alone realised a 60% decrease in the time taken to detect a crime and a 28.6% increase in efficiency on disaster resources with an overall spike in public satisfaction of 25.7%. Such findings improve the understanding of how this framework can increase urban efficiency, sustainability, and quality of life, which makes the solution usable in future smart city projects.

关键词： Waste reduction Energy consumption Costs Smart cities Disasters Memory Big Data Real-time systems Energy management systems Vehicle dynamics

来源：评论

学校读者我要写书评

暂无评论

Detection of Underground Object Using Ground Penetrating Radar

Detection of Underground Object Using Ground Penetrating Rad...

引用

international conference on Advanced Computing and Communication Systems (ICACCS)

作者： L. David William Raj Utsab Banerjee M. Thilagaraj A. Suganya U. Ramani C. Ganesh MVJ College of Engineering Bengalur MVJ College of Engineering Bengaluru India Dr. Mahalingam College of Engineering and Technology Pollachi India K. Ramakrishnan College of Engineering Trichy India Sri Eshwar College of Engineering Coimbatore India

This paper presents the applications for the detection of buried Improvised Explosive Devices (IEDs) and buried fusing mechanisms for the sake of national security. The instrument is used for the erection of buried images in Ground Penetrating Radar. The identified underground objects like skeletons, treasure, cables, mines etc. are potentially measured. During the collection of Ground Penetrating Radar raw images, the unwanted impurities, or elements such as noise and clutter are obtained. Raw images are also called B-Scan images, where the sampling rate is 8+ frames per seconds. The immense data for the pre-processing techniques has been preferred. The underground radar image signalized by the hyperbola which is reflected from the underground objects. The focused work is to clarify the interpretation of hyperbolic pattern present in Ground Penetrating Radar data and the curve fitting and the neural networks techniques are used to evaluate the position of the object.

关键词： Ground penetrating radar Impurities Neural networks Radar imaging parallel processing Skeleton Object recognition

来源：评论

学校读者我要写书评

暂无评论

Large Language Models and Adversarial Reinforcement Learning to Automate PLCs Programming: A Preliminary Investigation

Large Language Models and Adversarial Reinforcement Learning...

引用

international conference on Control, Decision and Information Technologies (CoDIT)

作者： Abderrahmane Boudribila Mohamed-Amine Chadi Abdelouahed Tajer Zakaria Boulghasoul Cadi Ayyad University National School of Applied Sciences Systems Engineering Applications Laboratory Marrakech Morocco Faculty of Sciences Semlalia Informatics Systems Engineering Laboratory Cadi Ayyad University Marrakech Morocco

The manual programming of Programmable Logic Controllers (PLCs) is a time-consuming and error-prone task, particularly for complex systems. Researchers have proposed various techniques, such as the modular, decentralized, hierarchical, and distributed approaches, which all fall under the Supervisory Control Theory (SCT) whose main goal is to generate a supervisor that ensures that the controller's behavior satisfies the specifications. While these techniques have demonstrated efficiency in systems of low complexity, high-complexity systems and probabilistic ones remain a major challenge. In this paper, we propose a novel pipeline that relies solely on Artificial Intelligence (AI)-techniques, namely, Reinforcement Learning (RL) and Natural Language processing (NLP) techniques, including Named Entity Recognition (NER) and Large Language Models (LLMs). As a preliminary result, we demonstrate the potential of the proposed pipeline using the recent ChatGPT model by making a sample dataset in this context and generating Structured Text code from specifications presented in a natural language format. Finally, we outline future directions toward a fully automated AI-based PLC programming tool.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Analysis of Offloading Computation in Mobile Edge Computing (MEC): A Survey

Analysis of Offloading Computation in Mobile Edge Computing ...

引用

international conference on parallel distributed and Grid Computing (PDGC)

作者： Aarti Sharma Chander Diwaker Mamtesh Nadiyan Computer Science … Engineering University Institute of Engineering and Technology Kurukshetra India Computer Science … Engineering National Institute of Technology Kurukshetra India

ISBN: (纸本)9781665454025

Smartphones have made resource-intensive mobile applications indispensable in everyday life. To meet predetermined requirements and lighten the weight of such challenges brought on by the swift expansion of such serving technologies, distributed mobile edge computing (MEC) was developed to bring compute environments closer to end-users, frequently in a single step. To bridge the gap between the two, offloading techniques have been developed in the literature to shift resource-intensive tasks from mobile devices to nearby servers. There are many new concerns in the MEC context that make compute offloading problems more complex than ever before. These include the inherent software and hardware heterogeneity, constraints, ecosystem dynamics, and stochastic behaviour. The research also took into account a number of indicators relevant to computation offloading strategies in MEC. In this research, we provide a review of computation offloading strategies in the MEC setting in order to identify existing methods on this important topic and to raise unresolved challenges. The survey concludes with a case study illustrating MEC's applicability in the medical field.

关键词： Multi-access edge computing Smart homes Software Mobile applications Servers Resource management Reliability

来源：评论

学校读者我要写书评

暂无评论

Cost-Effective Dynamic Alliance Pricing Mechanism Based on distributed Edge-Intelligence

Cost-Effective Dynamic Alliance Pricing Mechanism Based on D...

引用

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

作者： Zhihan Cao Xi Zheng Jianxiong Guo Weijia Jia Yang Xu Tian Wang Beijing Normal University Zhuhai China Fudan University Shanghai China Macquarie University Australia Hunan University Changsha China

In Internet of Thing (ToT) system based on edge intelligence, pay-for-use demand has become a consensus, and the pricing of ToT services has attracted the attention of academia and industry. The pricing method based on non-cooperative game allows edge service providers to compete fairly, effectively preventing edge nodes from malicious bidding. However, in this scenario, a task can only be assigned to one edge vendor. Because only one winner can profit each time, it is easy to create a large number of edge service providers who cannot profit for a long time due to insufficient incentives. To this end, a dynamic alliance pricing mechanism based on distributed edge-intelligence is proposed. Edge service providers can freely choose to form an edge dynamic alliance, which not only retains the independence of edge nodes, but also makes full use of the advantages of mutual cooperation between nodes. Tn order to prevent abnormal behaviors of edge nodes, we set up necessary restrictive rules. At the same time, we designed a privacy-enhanced joint pricing prediction algorithm to screen the alliance’s candidate solutions to improve pricing efficiency and edge benefit. The experimental results show that, compared with the traditional game method, the performance of the mechanism we proposed improves the utilization rate of edge resources by 32.76%-61.37%. Meanwhile, the prediction accuracy was improved by 16.47%38.86%, and the average prediction time was reduced by 42.81 %-65.57%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

STGE: Sensor Topology and Graph Embedding Learning with Heterogeneous Smart Environment 27

STGE: Sensor Topology and Graph Embedding Learning with Hete...

引用

27th IEEE international conference on parallel and distributed Systems, ICPADS 2021

作者： Wang, Xiao Zhang, Sheng Pan, Yi Lin, Zeyu Shenzhen International Graduate School Tsinghua University China Tsinghua University Department of Electronic Engineering China

ISBN: (纸本)9781665408783

In recent years, the Smart Environment(SE) supported by the Internet of Things(IoT) shows great ability to acquire and apply knowledge about an environment. Typical tasks in such environments are intended to monitor and predict the behavior patterns of residents. It would be helpful to these tasks if we can model the rich multi-model perceptional context and select the right combinations of sensory resources. In this study, we propose STGE, a novel sensor topology learning and graph embedding technique. STGE consists of two phases. 'ST' applies data-driven adjacency learning methods to acquire sensor logical topology, which helps to determine the combination of sensors. 'G E' learns representations of sensory resources based on the sensor topology, and leverages ideas of a novel graph embedding model called struct2vec. Through experiments with Smart Home(SH) data-sets, we demonstrate that STGE can achieve explainable and computable sensor's logical topology and their latent representation across different smart homes. The learned embedding is compatible with machine learning techniques, and can optimize the performance of downstream tasks such as human activity recognition. © 2021 IEEE.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

A Self-protecting Approach for Service-oriented Mobile applications 23

A Self-protecting Approach for Service-oriented Mobile Appli...

引用

23rd international conference on Enterprise Information Systems (ICEIS)

作者： Martins, Ronaldo Rodrigues de Oliveira Camargo, Marcos Paulo Passini, William Filisbino Campos, Gabriel Nagassaki Affonso, Frank Jose Sao Paulo State Univ UNESP Dept Stat Appl Math & Computat POB 178 BR-13506900 Rio Claro SP Brazil

ISBN: (纸本)9789897585098

The evolution of software systems in the last 10 years has brought new challenges for the development area, especially for service-oriented Mobile applications (MobApps). In the mobile computing domain, the integration of MobApps into service-based systems has been a feasible alternative to boost the capacity of processing and storage of such applications. In parallel, this type of application needs monitoring approaches mainly due to the need of dealing with a large number of users, continuous changes in the execution environment, and security threats. Besides that, most MobApps do not present the self-protecting property by default, resulting in a number of adverse situations, such as integrity of execution, reliability, security, and adaptations at runtime. The principal contribution of this paper is an approach based on MAPE-K (Monitor-Analyze-Plan-Execute over Knowledge) loop and machine learning techniques to ensure self-protecting features in MobApps, in particular, those based on services. Experimental results showed that this approach can autonomously and dynamically mitigate threats, making these applications more trustworthy and intrusion-safe. Our approach has good potential to contribute to the development of MobApps, going beyond existing approaches.

关键词： Self-protecting Mobile applications Web Service Security

来源：评论

学校读者我要写书评

暂无评论

Edge AI in 6G: Vision, Technologies, and applications

Edge AI in 6G: Vision, Technologies, and Applications

引用

Pervasive Computational Technologies (ICPCT), international conference on

作者： Vanessa Azucena Monzón Centeno Jesús Emilio Agustín Padilla Caballero Claudia Rossana Poma García Jonathan Orihuela Flores Wilmer Amado Huamán Malca Carlos Alberto Ferrando Gómez Escuela de Posgrado Universidad César Vallejo Lima Perú Pregrado Universidad Nacional de Educación Enrique Guzmán y Valle Lima Perú Pregrado Universidad Nacional del Callao Callao Perú

ISBN: (数字)9798331508685

ISBN: (纸本)9798331519476

The development of wireless connections is being pushed by an unprecedented rise of artificial intelligence (AI) software, with 6G becoming a game-changing technology. However advanced artificial intelligence (AI) needs a lot of connectivity and processing power, which causes delays, energy waste, network traffic, and privacy breaches. By combining sensing, interaction, computing, and intellect, Edge AI—which incorporates model learning and reasoning capacities at the connection's edge—offers an innovative approach for 6G network deployments. With an emphasis on distributed machine learning algorithms and incorporated wireless networking protocols, this article offers a vision for sustainable and reliable edge artificial intelligence (AI) systems. To fit edge AI, the article also covers novel design concepts, service-driven utilization techniques for optimizing, and a complete end-to-end system framework.

关键词： 6G mobile communication Wireless communication Wireless sensor networks Edge AI Telecommunication traffic Software Sensors Reliability Internet of Things Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

PE-FedAvg: A Privacy-Enhanced Federated Learning for distributed Android Malware Detection

PE-FedAvg: A Privacy-Enhanced Federated Learning for Distrib...

引用

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

作者： Junwei Tang Zilong Xu Luyao Ye Tao Peng Ruhan He Xinrong Hu Wenlong Tian Hubei Provincial Engineering Research Center for Intelligent Textile and Fashion Wuhan Textile University School of Computer Science and Artificial Intelligence Wuhan Textile University School of Computer Science University of South China School of Physical and Mathematical Sciences Nanyang Technological University Singapore

Android malware detection has become research hotspot in mobile security. When security service providers obtain feature information from target samples, they may involve user privacy information such as identity and behavioral habits, creating an urgent need for a distributed machine learning model to carry out malicious application detection with privacy protection. However, the information exchange between clients and servers in basic federated learning still poses risks of model data leakage, and the likelihood of inferring privacy information from the original feature data is high. Therefore, This paper propose a privacy-enhanced federated learning system called PE-FedAvg for distributed Android malware detection. Firstly, Gaussian noise is added to the feature data uploaded from the client to the server, satisfying differential privacy characteristics while retaining data distribution for privacy protection. Secondly, an improved homomorphic encryption algorithm based on modular repeated squaring is used to encrypt and transmit the gradient weight information exchanged between federated learning clients and servers, preventing model-targeted attacks. By conducting the experiments on the Drebin and Malgenome datasets, our design has demonstrated exceptional performance compared to the state-of-the-art work, achieving accuracy rates of 98.61% and 99.3%, respectively. This achievement highlights that our approach not only enhances the security of the federated learning system, but also more effectively accomplishes the detection of Android malware.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Unlocking Personalized Healthcare on Modern CPUs/GPUs: Three-way Gene Interaction Study

Unlocking Personalized Healthcare on Modern CPUs/GPUs: Three...

引用

international Symposium on parallel and distributed processing (IPDPS)

作者： Diogo Marques Rafael Campos Sergio Santander-Jimé nez Zakhar Matveev Leonel Sousa Aleksandar Ilic INESC-ID Instituto Superior T&#x00E9 cnico Universidade de Lisboa Portugal Polytechnic School University of Extremadura Spain Intel Corporation Russia

Developments in Genome-Wide Association Studies have led to the increasing notion that future healthcare techniques will be personalized to the patient, by relying on genetic tests to determine the risk of developing a disease. To this end, the detection of gene interactions that cause complex diseases constitutes an important application. Similarly to many applications in this field, extensive data sets containing genetic information for a series of patients are used (such as Single-Nucleotide Polymorphisms), leading to high computational complexity and memory utilization, thus constituting a major challenge when targeting high-performance execution in modern computing systems. To close this gap, this work proposes several novel approaches for the detection of three-way gene interactions in modern CPUs and GPUs, making use of different optimizations to fully exploit the target architectures. Crucial insights from the Cache-Aware Roofline Model are used to ensure the suitability of the applications to the computing devices. An extensive study of the architectural features of 13 CPU and GPU devices from all main vendors is also presented, allowing to understand the features relevant to obtain high-performance in this bioinformatics domain. To the best of our knowledge, this study is the first to perform such evaluation for epistasis detection. The proposed approaches are able to surpass the performance of state-of-the-art works in the tested platforms, achieving an average speedup of 3.9× (7.3× on CPUs and 2.8× on GPUs) and maximum speedup of 10.6× on Intel UHD P630 GPU.

关键词： Performance evaluation distributed processing Computational modeling Graphics processing units Genomics Medical services Computer architecture

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 << < 121 122 123 124 125 126 127 128 129 130 > >>

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：