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

1,560 篇 会议
1 篇 期刊文献

馆藏范围

1,561 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

884 篇 工学
- 764 篇 计算机科学与技术...
- 525 篇 软件工程
- 249 篇 信息与通信工程
- 192 篇 控制科学与工程
- 127 篇 电气工程
- 82 篇 网络空间安全
- 77 篇 生物医学工程（可授...
- 72 篇 安全科学与工程
- 63 篇 交通运输工程
- 61 篇 生物工程
- 55 篇 电子科学与技术（可...
- 44 篇 动力工程及工程热...
- 43 篇 仪器科学与技术
- 42 篇 石油与天然气工程
- 41 篇 光学工程
302 篇 理学
- 161 篇 数学
- 82 篇 生物学
- 71 篇 统计学（可授理学、...
- 60 篇 物理学
- 37 篇 系统科学
- 33 篇 化学
262 篇 管理学
- 199 篇 管理科学与工程(可...
- 104 篇 图书情报与档案管...
- 82 篇 工商管理
- 34 篇 公共管理
112 篇 医学
- 78 篇 临床医学
- 75 篇 公共卫生与预防医...
- 62 篇 基础医学(可授医学...
49 篇 法学
- 47 篇 社会学
37 篇 经济学
- 37 篇 应用经济学
18 篇 文学
15 篇 教育学
11 篇 农学
2 篇 军事学
1 篇 艺术学

主题

193 篇 data models
157 篇 accuracy
153 篇 computational mo...
92 篇 training
86 篇 feature extracti...
86 篇 machine learning
77 篇 predictive model...
69 篇 data mining
67 篇 deep learning
63 篇 real-time system...
57 篇 big data
49 篇 adaptation model...
45 篇 security
44 篇 robustness
41 篇 decision making
40 篇 convolutional ne...
39 篇 cloud computing
36 篇 analytical model...
35 篇 neural networks
34 篇 optimization

机构

14 篇 lovely professio...
7 篇 shandong provinc...
7 篇 key laboratory o...
6 篇 college of mecha...
6 篇 institute of aer...
5 篇 lloyd institute ...
5 篇 college of intel...
5 篇 national univers...
5 篇 department of co...
5 篇 shandong fundame...
5 篇 national univers...
5 篇 institute of aer...
4 篇 karnataka bangal...
4 篇 shanghai jiao to...
4 篇 school of comput...
4 篇 chitkara univers...
4 篇 new horizon coll...
4 篇 srm institute of...
4 篇 school of softwa...
4 篇 koneru lakshmaia...

作者

7 篇 nijhawan ginni
5 篇 jeanette miriam ...
5 篇 lu xiaobo
5 篇 singh navdeep
4 篇 nicola franco
4 篇 choudhry mani de...
4 篇 akhil karnam
4 篇 zhang rui
4 篇 yu zhang
4 篇 akshya j.
4 篇 lihui wang
4 篇 qu yuben
4 篇 wang lihui
4 篇 li lei
4 篇 dong chao
4 篇 dutt varun
4 篇 puri chetan
3 篇 yuangan wang
3 篇 junqi luo
3 篇 zhang lei

语言

1,452 篇 英文
108 篇 其他
3 篇 中文

检索条件"任意字段=2024 IEEE International Conference on Cognitive Computing and Complex Data"

共 1561 条记录，以下是31-40 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：

Research on the Application of Intelligent computing and Trustworthy Machine Learning in Financial complex Systems 6

Research on the Application of Intelligent Computing and Tru...

引用

6th international conference on data-Driven Optimization of complex Systems (DOCS)

作者： Liu, Zhiyi Zhang, Kai Zheng, Yejie Xu, Shaohua Qu, Jiaxin Eastmoney Informat Co Ltd Eastmoney AI Res Inst Shanghai Peoples R China Shanghai Artificial Intelligence Lab Shanghai Peoples R China East China Univ Sci & Technol Shanghai Peoples R China

ISBN: (纸本)9798350377859;9798350377842

The complexity of financial systems and the rapid increase in data volume are making the use of intelligent computing and trustworthy machine learning more important in finance. This paper discusses how intelligent computing can be applied within complex financial systems and takes a deeper look at the theory behind trustworthy machine learning and how it is used in finance. By combining the structure of complex networks with the computing power of machine learning, the paper also explores the inner workings of large neural networks and considers how to apply the theory of dynamic systems to the tuning of these networks, to improve intelligent computing in complex financial systems. Experiments based on the "scientific intelligence + machine conjecture" approach were carried out for risk assessment and market forecasting. The results show that these technologies can improve how financial institutions manage risk, help investors get more reliable information about market trends, and meet the transparency needed for regulatory compliance. The use of intelligent computing and trustworthy machine learning in complex financial systems points to a future with lots of potential for innovation and new opportunities.

关键词： Intelligent computing Trustworthy Machine Learning Financial complex Systems Fifth Paradigm

来源：评论

学校读者我要写书评

暂无评论

Energy-Efficient Deployment of Stateful FaaS Vertical Applications on Edge data Networks 33

Energy-Efficient Deployment of Stateful FaaS Vertical Applic...

引用

33rd ieee international conference on Computer Communications and Networks (ICCCN)

作者： Cicconetti, Claudio Bruno, Raffaele Passarella, Andrea CNR IIT Pisa Italy

ISBN: (纸本)9798350348439;9798350384611

5G and beyond support the deployment of vertical applications, which is particularly appealing in combination with network slicing and edge computing to create a logically isolated environment for executing customer services. Even if serverless computing has gained significant interest as a cloud-native technology its adoption at the edge is lagging, especially because of the need to support stateful tasks, which are commonplace in, e.g., cognitive services, but not fully amenable to being deployed on limited and decentralized computing infrastructures. In this work, we study the emerging paradigm of stateful Function as a Service (FaaS) with lightweight task abstractions in WebAssembly. Specifically, we assess the implications of deploying inter-dependent tasks with an internal state on edge computing resources using a stateless vs. stateful approach and then derive a mathematical model to estimate the energy consumption of a workload with given characteristics, considering the power used for both processing and communication. The model is used in extensive simulations to determine the impact of key factors and assess the energy trade-offs of stateless vs. stateful.

关键词： Stateful FaaS Local data Networks Beyond 5G Vertical Applications Serverless computing

来源：评论

学校读者我要写书评

暂无评论

cognitive computing in Intelligent Traffic Management Systems 3

Cognitive Computing in Intelligent Traffic Management System...

引用

international conference on Advances in computing, Communication and Applied Informatics (ACCAI)

作者： Sudhakar, A. V. V. Tyagi, Anuj Patil, Pallavi Sachin Kumar, K. Suresh Sathe, Manoj Geetha, B. T. SR Univ Sch Engn Dept EEE Warangal Telangana India Northeastern Univ Boston MA 02115 USA Savitribai Phule Pune Univ Genba Sopanrao Moze Coll Engn Dept Artificial Intelligence & Machine Learning Pune 45 Maharashtra India Panimalar Engn Coll Chennai 600123 Tamil Nadu India PES Modern Inst Business StudiesPune Comp Sci Pune Maharashtra India Saveetha Univ SIMATS Saveetha Sch Engn Dept ECE Chennai Tamil Nadu India

ISBN: (纸本)9798350389432;9798350389449;9798350389456

Intelligent business operation systems are undergoing a revolution as a result of cognitive computing, which is boosting their capacity to analyze large amounts of data and produce well-informed conclusions in real-time. The purpose of this investigation is to investigate the possibility of incorporating cognitive computing technologies, such as machine literacy, natural language processing, and big data analytics, into business operation systems to address the issue of civic traffic, improve the flow of business, and enhance safety. The development of adaptive business control mechanisms that can respond robustly to changing business situations is made possible by cognitive computing. This is accomplished through the use of sophisticated algorithms and predictive analytics. The purpose of this article is to investigate case studies and real-world implementations, to highlight the major improvements in company efficiency and decrease in travel times that may be realized using cognitive computing. The findings provide evidence that cognitive computing has the potential to transform conventional business operation systems into intelligent, responsive networks that are capable of tone-optimization. This would result in the creation of civic environments that are more intelligent and more environmentally sustainable.

关键词： cognitive computing intelligent traffic management urban congestion adaptive traffic control predictive analytics

来源：评论

学校读者我要写书评

暂无评论

Quantum Machine Learning in the cognitive Domain: Alzheimer's Disease Study

Quantum Machine Learning in the Cognitive Domain: Alzheimer'...

引用

2024 ieee High Performance Extreme computing conference, HPEC 2024

作者： Akpinar, Emine Yildiz Technical University Department of Physics Istanbul Turkey

ISBN: (纸本)9798350387131

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder, primarily affecting the elderly population and leading to significant cognitive decline. This decline manifests in various mental faculties such as attention, memory, and higher-order cognitive functions, severely impacting an individual's ability to comprehend information, acquire new knowledge, and communicate effectively. One of the tasks influenced by cognitive impairments is handwriting. By analyzing specific features of handwriting, including pressure, velocity, and spatial organization, researchers can detect subtle changes that may indicate early-stage cognitive impairments, particularly AD. Recent developments in classical artificial intelligence (AI) methods have shown promise in detecting AD through handwriting analysis. However, as the dataset size increases, these AI approaches demand greater computational resources, and diagnoses are often affected by limited classical vector spaces and feature correlations. Recent studies have shown that quantum computing technologies, developed by harnessing the unique properties of quantum particles such as superposition and entanglement, can not only address the aforementioned problems but also accelerate complex data analysis and enable more efficient processing of large datasets. In this study, we propose a variational quantum classifier with fewer circuit elements to facilitate early AD diagnosis based on handwriting data. Our model has demonstrated comparable classification performance to classical methods and underscores the potential of quantum computing models in addressing cognitive problems, paving the way for future research in this domain. © 2024 ieee.

关键词： Vector spaces

来源：评论

学校读者我要写书评

暂无评论

Model-Based Approach for Efficient data Exploitation Process in IoT Systems 20

Model-Based Approach for Efficient Data Exploitation Process...

引用

20th ieee international Wireless Communications and Mobile computing (ieee IWCMC) - Green and Intelligent Communications

作者： Terracher, Audrey Kocik, Remy Hamouche, Redha Rachedi, Abderrezak Bourouina, Tarik Univ Gustave Eiffel ESYCOM CNRS UMR9007 ESIEE Paris Noisy Le Grand France Univ Gustave Eiffel LIGM Lab CNRS UMR8049 Champs Sur Marne France

ISBN: (纸本)9798350361261;9798350361278

Nowadays, sensor networks are used in various fields and for multiple purposes in medicine, agriculture or industry. In a network, different kinds of sensors are often involved. This heterogeneity makes it complex and time-consuming to implement the exploitation of the data acquired by these sensor networks. We notice a growing need for scalable and rapidly deployable infrastructures to allow for interoperability for the processing, the storage or visualization of collected data. Faced with these challenges, we define a framework to facilitate the automatic deployment of data exploitation applications in heterogeneous sensor networks. We propose a Model-Driven Engineering-based approach that provides a high-level model to describe such infrastructures. Along with automatic code generation, our model aims to facilitate the exploitation of collected data through a graphical interface. The model we define allows for the description of heterogeneous sensor networks with a data exploitation point of view.

关键词： IoT data exploitation Model-Driven Engineering Sensor Networks Metamodeling Code Generation

来源：评论

学校读者我要写书评

暂无评论

cognitive computing with Deep Learning based Cybersecurity Solution for Human Computer Interface Applications 2

Cognitive Computing with Deep Learning based Cybersecurity S...

引用

2nd ieee international conference on data Science and Network Security, ICDSNS 2024

作者： Srivastava, Aviral Stager, Sarah College of Ist Pennsylvania State University United States

ISBN: (纸本)9798350373110

In the rapidly evolving domain of cybersecurity, the gap between the need for skilled professionals and the available workforce is widening, with over 35,000 open positions in cyber roles. This challenge is compounded by the intense focus and memory demands of cybersecurity tasks. Our research introduces a novel approach that bridges this gap through a mathematical solution, enhancing the trust and reliability in human-machine collaboration for cybersecurity in Human-Computer Interface (HCI) applications. We present a dynamic arithmetic optimization algorithm with a deep learning-based cybersecurity solution (DAOA-DLCS), which integrates cognitive computing and deep learning (DL) techniques. This innovative approach not only sustains cybersecurity but also advances it by leveraging cognitive systems capable of learning and adapting. The DAOA-DLCS technique fosters active threat recognition, rapid incident response, and dynamic adaptation to new threats, thereby improving user authentication and behavior analysis. This leads to a secure, seamless, and tailored user experience, addressing the constraints of limited human resources in cybersecurity roles. Our solution enhances the trustworthiness and autonomy in human-machine teaming, with the DAOA-DLCS technique employing min-max normalization to scale input data, an LSTM model for precise intrusion detection and classification, and DAOA-based hyperparameter tuning for optimal LSTM model selection. Tested on a benchmark dataset, the DAOA-DLCS technique demonstrates superior performance over existing systems in various measures, marking a significant step towards reliable and autonomous cybersecurity solutions in complex socio-technical systems. © 2024 ieee.

关键词： Cybersecurity

来源：评论

学校读者我要写书评

暂无评论

Minimizing data Transmission Delay in Vehicular Networks through Network Coding-based Broadcasting 17

Minimizing Data Transmission Delay in Vehicular Networks thr...

引用

ieee Congress on Cybermatics: 17th ieee international conference on Internet of Things, iThings 2024, 20th ieee international conference on Green computing and Communications, GreenCom 2024, 17th ieee international conference on Cyber, Physical and Social computing, CPSCom 2024, 10th ieee international conference on Smart data, Smartdata 2024

作者： Hu, Jiali Qu, Long Song, Qinglin Zhu, Ran Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China Zhejiang Faraday Laser Technology co. Ltd Wenzhou325024 China

ISBN: (纸本)9798350351637

Advances in wireless communication technology have facilitated the development of vehicular networks. Intelligent vehicles are able to realize a variety of applications and services to enhance the driving experience through Vehicle-to-Everything (V2X) communication. However, meeting the requirement of low latency in dynamic and complex vehicular environments poses a challenge. This paper presents a network coding framework based on a vehicular network data transmission model, aiming to reduce transmission latency and data dropout rate by encoding and broadcasting packets at Roadside Units (RSUs). Due to the mobility of vehicles, interference becomes more complex. To mitigate interference between data transmissions, we employ dynamic power control. However, the optimization problem involved is a mixed integer problem. To reduce the complexity, this paper introduces a Column Generation algorithm to solve the model. The algorithm decomposes the problem into a pricing problem responsible for packet scheduling and a master problem responsible for minimizing the transmission delay to find the optimal coding opportunities and broadcasting strategies for vehicle packets. Experimental results demonstrate that compared to scenarios without network coding, the proposed algorithm reduces transmission latency by 5.694% and decreases data dropout rate by 7.143%. © 2024 ieee.

关键词： Network coding

来源：评论

学校读者我要写书评

暂无评论

A Generic Performance Metric for Scientific data Compression 20

A Generic Performance Metric for Scientific Data Compression

引用

20th ieee international conference on E-Science (E-Science)

作者： Qin, Zhenlu Gu, Jessie Liu, Maggie Wang, Jinzhen Zhu, Hongjian AUM Montgomery AL 36117 USA Univ Maryland College Pk MD 20742 USA Tenafly High Sch Tenafly NJ USA Univ N Carolina Charlotte NC USA X Byte Res Tenafly NJ USA

ISBN: (纸本)9798350365627;9798350365610

The performance outcomes of scientific data compression are complex in nature, often with one performance metric being more prioritized/optimized over others in the algorithm. To balance between different performance metrics, this paper formulates a new generic metric and uses it for searching an optimal configuration that leads to a balanced compression performance.

关键词： data compression high-performance computing performance

来源：评论

学校读者我要写书评

暂无评论

Swarm Intelligence-Based Dynamic Virtual Machine Placement Optimization in Cloud data Centers 1

Swarm Intelligence-Based Dynamic Virtual Machine Placement O...

引用

1st ieee international conference on Advances in computing, Communication and Networking, ICAC2N 2024

作者： Mishra, Sanjay Awasthi, Monisha Uttaranchal University Uttaranchal School of Computing Science Dehradun India

ISBN: (纸本)9798350356816

Virtual machine (VM) deployment is a critical aspect of cloud data center resource management that directly impacts performance, energy efficiency, and quality of service. Efficient VM deployment ensures optimal resource utilization, reduces power consumption, and lowers operating costs. However, the dynamic nature of cloud environments poses significant challenges to achieving optimal VM deployment. This study presents various intelligences, especially partial swarm optimization (PSO), as a powerful optimization technique for dynamic VM deployment. Many cognitive algorithms mimic the collective behavior of social organisms and provide an efficient approach to solving complex optimization problems. This study addresses the issue of deploying virtual machines to maximize resource utilization while reducing power consumption and ensuring quality of service. Extensive simulation shows that the proposed PSO-based method significantly outperforms conventional static and heuristic approaches regarding energy efficiency, resource utilization, and SLA compliance. The results show the potential of multiple intelligences in improving the operational efficiency of cloud data centers, leading to future research and practical implementation in dynamic cloud environments. © 2024 ieee.

关键词： Quality of service

来源：评论

学校读者我要写书评

暂无评论

Lightweight Spiking Neural Network based Detector for Interweave cognitive Radios 59

Lightweight Spiking Neural Network based Detector for Interw...

引用

59th Annual ieee international conference on Communications (ieee ICC)

作者： Galib, Md Mehedi Hassan Younis, Mohamed Ahmed, Sultan Univ Maryland Baltimore Cty Dept Comp Sci & Elect & Engn Baltimore MD 21250 USA Univ Maryland Baltimore Cty Dept Informat Syst Baltimore MD 21250 USA

ISBN: (纸本)9781728190549

The major advances in wireless communication technology have led to increased adoption across almost all application domains. However, the massive growth has caused spectrum scarcity despite the fact that many of the frequency bands are not fully-utilized. cognitive radios have emerged as a viable means to support dynamic spectrum access. Particularly, supporting opportunistic access through passive spectrum monitoring is of great interest. Existing techniques for detecting white space either require modification to commodity radio transceivers, or involve computationally complex models that do not suit resource-constrained devices. This paper opts to fill the technical gap by proposing a novel lightweight white space detector that employs spiking neural networks (SNN). SNN is a bio-inspired technique for creating data-driven models. The proposed design relies on the sensed energy in the medium to determine whether a primary user is active. The validation results using live LTE data demonstrate the effectiveness of our novel detector. Suitability for edge devices is confirmed through implementation on a Raspberry-PI platform.

关键词： cognitive radios Spectrum sensing Spike neural network Opportunistic communications

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157页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：