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

584 篇 会议
117 篇 期刊文献
6 册 图书

馆藏范围

707 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

425 篇 工学
- 234 篇 计算机科学与技术...
- 187 篇 软件工程
- 144 篇 控制科学与工程
- 92 篇 电气工程
- 70 篇 电子科学与技术（可...
- 56 篇 信息与通信工程
- 48 篇 机械工程
- 31 篇 光学工程
- 31 篇 动力工程及工程热...
- 27 篇 生物医学工程（可授...
- 26 篇 生物工程
- 24 篇 仪器科学与技术
- 18 篇 力学（可授工学、理...
- 17 篇 航空宇航科学与技...
- 15 篇 建筑学
- 14 篇 化学工程与技术
- 13 篇 交通运输工程
- 12 篇 冶金工程
238 篇 理学
- 154 篇 数学
- 61 篇 物理学
- 48 篇 系统科学
- 37 篇 统计学（可授理学、...
- 25 篇 生物学
- 13 篇 化学
83 篇 管理学
- 60 篇 管理科学与工程(可...
- 25 篇 图书情报与档案管...
- 24 篇 工商管理
18 篇 医学
- 15 篇 临床医学
- 13 篇 基础医学(可授医学...
- 13 篇 药学(可授医学、理...
8 篇 法学
6 篇 教育学
6 篇 农学
4 篇 经济学
2 篇 军事学

主题

19 篇 optimization
16 篇 accuracy
15 篇 computational mo...
15 篇 feature extracti...
12 篇 automation
11 篇 control systems
11 篇 mathematical mod...
10 篇 predictive model...
10 篇 simulated anneal...
10 篇 fault detection
10 篇 training
9 篇 energy consumpti...
9 篇 servers
9 篇 particle swarm o...
9 篇 genetic algorith...
9 篇 uncertainty
9 篇 controllers
8 篇 deep learning
8 篇 mobile edge comp...
8 篇 robots

机构

52 篇 school of automa...
25 篇 college of compu...
13 篇 dept. of electri...
12 篇 faculty of infor...
12 篇 southern methodi...
12 篇 new jersey insti...
12 篇 dept. of compute...
11 篇 beijing universi...
10 篇 cssc systems eng...
8 篇 dept. of automat...
8 篇 dept. of automat...
8 篇 dept. of softwar...
7 篇 firat university...
7 篇 dept. of compute...
6 篇 department of au...
6 篇 department of au...
5 篇 firat university...
5 篇 dept. of compute...
5 篇 dept. of electro...
4 篇 dept. of electri...

作者

26 篇 yuan haitao
25 篇 haitao yuan
24 篇 jia zhang
24 篇 bi jing
24 篇 zhang jia
23 篇 jing bi
15 篇 zhou mengchu
13 篇 mengchu zhou
13 篇 faisal h. khan
10 篇 baranyi péter
9 篇 kaya buket
8 篇 buket kaya
8 篇 korondi péter
8 篇 valeriy vyatkin
8 篇 chen-wei yang
8 篇 bin wu
7 篇 mohammed khorshe...
7 篇 seppo sierla
7 篇 sang-hoon lee
7 篇 kaya mehmet

语言

675 篇 英文
27 篇 中文
5 篇 其他

检索条件"机构=dept. Automation and Computer Engineering"

共 707 条记录，以下是21-30 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：

Brain Stroke Detection from CT Images using Transfer Learning Method 13

Brain Stroke Detection from CT Images using Transfer Learnin...

引用

13th International Conference on Advanced computer Information Technologies, ACIT 2023

作者： Çinar, Necip Kaya, Buket Kaya, Mehmet Dicle University Department of Computer Engineering Diyabakir Turkey Firat University Department of Electronics and Automation Elaziǧ Turkey Firat University Dept. of Computer Engineering Elaziǧ Turkey

Recently, with the production of high-capacity computers, artificial intelligence methods have been used in many areas. In particular, in the field of health, artificial intelligence methods are used to detect diseases and determine the treatments to be applied. Deep learning methods, a sub-branch of artificial intelligence, show a high success in diagnosing many diseases thanks to its deep CNN networks. In this study, firstly, it was tried to determine which deep learning methods are more successful for the detection of brain stroke from computerized tomography images. This study is of great importance in terms of determining which deep learning architectures we will focus on in our future studies on brain stroke. In this study, brain stroke disease was detected from CT images by using the five most common used models in the field of image processing, one of the deep learning methods. The pre-trained ResNetl01, VGG19, EfficientNet-B0, MobileNet-V2 and GoogleNet models were run with the same dataset and same parameters. As a result, the EfficientNet-B0 architecture showed the highest performance with 97.93% accuracy. ResNetl01, VGG19, MobileNet-V2 and GoogleNet models showed 94.32%, 97.28%, 92.30% and 91.61% accuracy rates, respectively. With this study, it was concluded that the EfficientNet architecture is more suitable for the detection of brain stroke disease from CT images. © 2023 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Data Efficient Safe Reinforcement Learning

Data Efficient Safe Reinforcement Learning

引用

2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Padakandla, Sindhu Prabuchandran, J.K. Ganguly, Sourav Bhatnagar, Shalabh Indian Institute of Science Dept. of Computer Science and Automation India Iit Dharwad Dept. of Computer Science Engineering India

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Applying reinforcement learning (RL) methods for real world applications pose multiple challenges - the foremost being safety of the system controlled by the learning agent and the learning efficiency. An RL agent learns to control a system by exploring the available actions in various operating states. In some states, when the RL agent exercises an exploratory action, the system may enter unsafe operation, which can lead to safety hazards both for the system as well as for humans supervising the system. RL algorithms thus must learn to control the system respecting safety. In this work, we formulate the safe RL problem in the constrained off-policy setting that facilitates safe exploration by the RL agent. We then develop a sample efficient algorithm utilizing the cross-entropy method. The proposed algorithm's safety performance is evaluated numerically on benchmark RL problems. © 2022 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Ontology Mapping-Based Semantic Reasoning with OPC UA for Heterogeneous Industrial Devices

Ontology Mapping-Based Semantic Reasoning with OPC UA for He...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Bi, Jing Wu, Rina Yuan, Haitao Wang, Ziqi Zhang, Jia Zhou, MengChu College of Computer Beijing University of Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Southern Methodist University Dept. of Computer Science in Lyle School of Engineering DallasTX United States New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ United States

ISBN: (纸本)9781665410205

The advent of smart manufacturing in Industry 4.0 signifies the arrival of the era of connections. As an excellent communication protocol, Object linking and embedding for Process Control Unified Architecture (OPC UA) can address most semantic heterogeneity issues. However, its semantics are not formally defined at the application layer. To address the information silo problem caused by semantic heterogeneity, a method named Querying of Ontology Mapping-based OPC UA (QOMOU) is proposed. It extracts the information models of OPC UA servers into resource description framework triples, utilizes web ontology language for semantic enrichment and inference, and employs a semantic similarity model for event ontology mapping to improve query efficiency. The method's effectiveness is validated through functional queries using the SPARQL protocol in Apache Jena. The query efficiency is 5% higher on average compared to both structured query and extensible markup languages. Moreover, by employing a keyword-matching algorithm, the query accuracy of the existing heterogeneous data integration scheme is improved by 4% on average. This enhancement can boost the operational efficiency of Internet of Things systems based on the OPC UA architecture. © 2024 IEEE.

关键词： Structured Query Language

来源：评论

学校读者我要写书评

暂无评论

Multi-Indicator Water Quality Prediction Using Multimodal Bottleneck Fusion and ITransformer with Attention

Multi-Indicator Water Quality Prediction Using Multimodal Bo...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Bi, Jing Li, Yibo Zhang, Xuan Yuan, Haitao Wang, Ziqi Zhang, Jia Zhou, MengChu College of Computer Beijing University of Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Southern Methodist University Dept. of Computer Science in Lyle School of Engineering DallasTX United States New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ United States

ISBN: (纸本)9781665410205

Water quality prediction methods forecast the future short or long-term trends of its changes, providing proactive advice for water pollution prevention and control. Existing water quality prediction methods only consider the historical data of single-type or multi-type water quality. However, meteorology and other factors also have a significant impact on water quality indicators. Therefore, only considering the historical data of water quality is not feasible. Unlike existing studies, this work proposes a hybrid water quality prediction model called CMI to solve the above problem. Before prediction, CMI incorporates a multimodal fusion mechanism of water quality time series and remote sensing images of meteorological rainfall. Moreover, CMI integrates the model of ConvNeXt V2 and a multimodal bottleneck transformer to extract image features for fusing the time series and images. Furthermore, it utilizes an emerging model of iTransformer to realize prediction with the fused features. Experimental results with real-life water quality time series and remotely sensed rainfall images demonstrate that CMI outperforms other state-of-the-art fusion algorithms, and the water quality prediction accuracy with fused meteorological data is 13% higher on average than that with only water quality time series. © 2024 IEEE.

关键词： Rain

来源：评论

学校读者我要写书评

暂无评论

Asymptotic Stability Preservation of Input Delayed Nonlinear Systems under Sampled-Data Feedback 63

Asymptotic Stability Preservation of Input Delayed Nonlinear...

引用

63rd IEEE Conference on Decision and Control, CDC 2024

作者： Yu, Xin Lin, Wei Jiangsu Normal University School of Electrical Engineering and Automation Xuzhou221116 China Case Western Reserve University Dept. of Electrical Systems and Computer Engineering ClevelandOH United States

ISBN: (纸本)9798350316339

We study the problem of global asymptotic stability preservation (GASP) for C0 non-smoothly stabilizable systems with input delay under sampled-data feedback. With the aid of Halanay inequality and the notion of homogeneity, the following sampled-data control results are established under a fast sampling: 1) GAS is preservable if the nonlinear system is homogeneous of degree zero and globally asymptotically stabilizable by homogeneous feedback;2) As a consequence, GAS via sampled-data feedback is achieved for a class of non-smoothly stabilizable systems with input delay in a lower-triangular or upper-triangular form. © 2024 IEEE.

关键词： Delay control systems

来源：评论

学校读者我要写书评

暂无评论

Energy and Time-Optimized Task Scheduling with Simulated-Annealing-Based Firefly Algorithm in Hybrid Cloud Edge Computing

Energy and Time-Optimized Task Scheduling with Simulated-Ann...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Bi, Jing Zhou, Xinmin Yuan, Haitao Zhang, Jia Zhou, MengChu College of Computer Beijing University of Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Southern Methodist University Dept. of Computer Science DallasTX75275 United States New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ07102 United States

ISBN: (纸本)9781665410205

In a cloud-edge system, data analysis, processing, and storage can be performed in edge servers, avoiding transferring data to more distant cloud servers. This greatly improves the efficiency of data processing, saves network bandwidth and cloud resources, and reduces operating and maintenance costs. However, it is a challenge of how to perform task scheduling. It is difficult to schedule tasks for joint optimization of the total energy consumption and completion time of a task sequence within a limited time in a resource-constrained cloud-edge system. The work proposes an improved Simulated-Annealing-based Firefly Algorithm with Linear position update, called SAFAL for short. SAFAL incorporates a simulated annealing mechanism and an efficient position update strategy into the firefly algorithm, enabling fireflies to find the optimal solution more quickly and avoid getting trapped in local optima. SAFAL adopts a probabilistic mapping operator to map the position of each firefly to a task scheduling sequence, thus linking the firefly space and the task space. Several test instances in cloud-edge systems are designed to validate the superiority of SAFAL over the firefly algorithm, simulated annealing, and firefly algorithm with a self-adaptive strategy. Results show that the weighted cost of total energy consumption and completion time of SAFAL is reduced by 16.32%, 17.62%, and 14.21%, respectively, with 20 tasks. © 2024 IEEE.

关键词： Simulated annealing

来源：评论

学校读者我要写书评

暂无评论

Multi-User Computation Offloading in Mobile Edge Computing with Hybrid Whale Optimization

Multi-User Computation Offloading in Mobile Edge Computing w...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Bil, Jing Li, Ning Yuan, Haitao Zhang, Jia Zhou, MengChu College of Computer Beijing University of Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Southern Methodist University Dept. of Computer Science DallasTX75275 United States New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ07102 United States

ISBN: (纸本)9781665410205

With the increasing amount of data and the need for real-time processing, Mobile Edge Computing (MEC) is growing rapidly, driving the shift from traditional cloud computing to distributed edge architectures. When offloading these applications with large amounts of data on mobile devices, a lot of computing and storage resources and high energy consumption are required. Yet, mobile devices' computing power, resource storage, and battery power are often limited and cannot meet these needs. To solve a computation offloading problem for joint optimization of time, cost, and energy, this work proposes an improved hybrid algorithm called Chaos and Lévy flights-based Whale Optimization Algorithm (CLWOA) to solve the multi-user offloading problem in an MEC-Cloud system. Each task is offloaded to local processors of mobile devices, edge servers, and cloud servers in proportion to jointly minimize the completion time, energy consumption, and total cost. Finally, compared with the whale optimization algorithm, lévy flight whale optimization algorithm, refined whale optimization algorithm, and chaos-based whale optimization algorithm, CLWOA reduces the weighted cost by 1.89%, 0.31%, 0.19%, and 0.42%, respectively. © 2024 IEEE.

关键词： Mobile edge computing

来源：评论

学校读者我要写书评

暂无评论

Monitoring and Forecasting Quality Indicators of Predough Production in the Bakery Industry 5

Monitoring and Forecasting Quality Indicators of Predough Pr...

引用

5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Lutska, Nataliia Zaiets, Nataliia Vlasenko, Lidiia Zhyltsov, Andrii Dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine Dept. of Electromagnetic Systems The Institute of Electrodynamics The National Academy of Sciences of Ukraine Kyiv Ukraine

ISBN: (纸本)9798350384499

The work demonstrates the process of developing a machine learning model for a system for monitoring and controlling the quality of predough at a bakery. This system will provide continuous analysis of the predough parameters, such as temperature, humidity, lifting force and titranic acidity, which will ensure timely detection of deviations in the quality of the predough and avoid production problems. In addition, it will help automate the quality control process and ensure the stability of production processes. Analysis and forecasting of dough parameters will improve the quality of produced bread or other bakery products. Management based also on the predicted values of technological indicators of the predough will allow the enterprise to avoid unnecessary costs of materials and energy and increase economic efficiency. As part of the study, seven machine learning models were created and reviewed, including three linear and four varieties of binary decision trees. An analysis of the best model - a regression decision tree - was carried out, confirming its effectiveness and the validity of the resulting hierarchical structure, in particular, the prediction of important indicators of predough with a high degree of reliability, which indicates its importance in practical applications in production. The created model can be used to monitor and control product quality in real time, allowing operators to quickly identify and correct any deviations in process performance. Also, by analyzing changes in the variables of the predough production process, it is possible to identify precursors of possible production accidents or deviations in product quality, which will allow timely measures to be taken to avoid them. ©2024 IEEE.

关键词： Bakeries

来源：评论

学校读者我要写书评

暂无评论

Energy-Optimized Task Offloading with Genetic Simulated-Annealing-Based PSO for Heterogeneous Edge and Cloud Computing

Energy-Optimized Task Offloading with Genetic Simulated-Anne...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Yuan, Haitao Zheng, Ziyue Bi, Jing Zhang, Jia Zhou, MengChu School of Automation Science and Electrical Engineering Beihang University Beijing100191 China College of Computer Beijing University of Technology Beijing100124 China Southern Methodist University Dept. of Computer Science DallasTX75275 United States New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ07102 United States

ISBN: (纸本)9781665410205

Recent years have seen a surge in Internet of Things (IoT) technologies, with billions of mobile devices (MDs) straining limited computing and networking resources. Mobile edge computing offloads tasks from MDs to edge servers, saving energy and reducing network pressure. Edge servers provide closer services yet have fewer resources than cloud servers. A new heterogeneous edge and cloud computing paradigm combines the benefits of both. Edge servers provide close proximity services to MDs, while the cloud owns enough resources. The existence of mobile IoT devices makes it more practical to consider mobility when allocating resources of edge servers to decrease the energy consumption of the heterogeneous edge and cloud while meeting the latency needs of tasks. This work formulate a constrained energy consumption optimization problem and design a hybrid algorithm named Genetic Simulated-annealing-based particle swarm optimization (PSO) to yield a near-optimal solution. Simulation results prove that compared to genetic algorithm, PSO, simulated-annealing-based PSO, and Trex, GSPSO reduces the total energy consumption by 38.64%, 54.63%, 45.94%, and 36.21%, respectively. © 2024 IEEE.

关键词： Mobile edge computing

来源：评论

学校读者我要写书评

暂无评论

Energy-Optimized Computation Offloading with Improved Differential Evolution in UAV-Enabled Edge and Cloud Computing

Energy-Optimized Computation Offloading with Improved Differ...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Yuan, Haitao Wang, Meijia Bi, Jing Zhang, Jia Zhou, MengChu School of Automation Science and Electrical Engineering Beihang University Beijing100191 China College of Computer Beijing University of Technology Beijing100124 China Southern Methodist University Dept. of Computer Science DallasTX75275 United States New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ07102 United States

ISBN: (纸本)9781665410205

Mobile edge computing (MEC) emerges as a vital paradigm to support the increasing use of mobile users (MUs) with capabilities similar to cloud computing. While most research concentrates on MEC facilitated by terrestrial base stations (BSs), its applicability in scenarios such as disaster rescue and field operations is limited. Efforts have been made to explore MEC assisted by unmanned aerial vehicles (UAVs) with efficient scheduling algorithms. However, relying solely on UAVs for MEC has limitations, particularly for computation-intensive applications. This work proposes a hybrid MEC system lever-aging UAVs and BS. Multiple UAVs and a BS are deployed to provide MEC services directly from UAVs or indirectly from the BS. We formulate an energy-efficient scheduling problem to minimize energy consumption by jointly optimizing UAV trajectories, task associations, and allocation of computing and transmitting resources. To solve it, this work designs a hybrid algorithm named _S_uccess History-based parameter Adaptation for Differential volution with a Niching-based population size reduction strategy and an efficient nsemble sinusoidal scheme (SHADE-NE). Experimental results validate the superiority of SHADE-NE over its benchmark peers, thus proving that SHADE-NE greatly enhances the performance of the system. © 2024 IEEE.

关键词： Computation offloading

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71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：