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

41,181 篇 会议
6,914 篇 期刊文献
318 册 图书

馆藏范围

48,413 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

29,960 篇 工学
- 17,996 篇 计算机科学与技术...
- 14,896 篇 软件工程
- 8,176 篇 信息与通信工程
- 5,800 篇 电子科学与技术（可...
- 5,564 篇 电气工程
- 5,077 篇 控制科学与工程
- 2,621 篇 生物工程
- 2,332 篇 光学工程
- 2,228 篇 生物医学工程（可授...
- 2,040 篇 机械工程
- 2,026 篇 动力工程及工程热...
- 1,928 篇 仪器科学与技术
- 1,503 篇 化学工程与技术
- 1,168 篇 材料科学与工程（可...
- 914 篇 安全科学与工程
- 885 篇 交通运输工程
- 780 篇 建筑学
15,728 篇 理学
- 8,313 篇 数学
- 5,233 篇 物理学
- 2,851 篇 生物学
- 2,682 篇 统计学（可授理学、...
- 1,927 篇 系统科学
- 1,570 篇 化学
6,144 篇 管理学
- 3,757 篇 管理科学与工程(可...
- 2,615 篇 图书情报与档案管...
- 2,115 篇 工商管理
1,712 篇 医学
- 1,497 篇 临床医学
- 1,387 篇 基础医学(可授医学...
- 927 篇 药学(可授医学、理...
1,095 篇 法学
- 898 篇 社会学
772 篇 经济学
527 篇 教育学
474 篇 农学
193 篇 文学
126 篇 军事学
47 篇 艺术学
3 篇 哲学
1 篇 历史学

主题

1,041 篇 computational mo...
1,011 篇 accuracy
798 篇 feature extracti...
747 篇 training
727 篇 computer science
539 篇 deep learning
502 篇 optimization
485 篇 machine learning
466 篇 predictive model...
461 篇 real-time system...
427 篇 support vector m...
411 篇 internet of thin...
401 篇 computer archite...
377 篇 data models
364 篇 neural networks
362 篇 bandwidth
346 篇 reliability
330 篇 mathematical mod...
319 篇 robustness
303 篇 wireless sensor ...

机构

170 篇 dept. of electri...
83 篇 institut univers...
82 篇 north-west unive...
80 篇 national centre ...
79 篇 infn sezione di ...
76 篇 infn sezione di ...
69 篇 institute of inf...
66 篇 università di ca...
62 篇 dept. of electr....
58 篇 dept. of electri...
57 篇 dept. of informa...
56 篇 dept. of compute...
53 篇 leiden universit...
52 篇 dept. of electri...
52 篇 school of automa...
51 篇 tno technical sc...
45 篇 université de st...
44 篇 dept. of compute...
43 篇 dept. of electri...
42 篇 infn lnf via enr...

作者

85 篇 ferrara g.
85 篇 ardid m.
85 篇 gal t.
84 篇 calvo d.
84 篇 bozza c.
81 篇 chen a.
78 篇 kalekin o.
72 篇 díaz a.f.
66 篇 huang f.
64 篇 boumaaza j.
55 篇 coleiro a.
52 篇 kulikovskiy v.
49 篇 gozzini s.r.
41 篇 benoit d.m.
41 篇 eddymaoui a.
40 篇 gagliardini s.
40 篇 labalme m.
37 篇 androulakis g.
35 篇 khatun a.
35 篇 del burgo r.

语言

44,112 篇 英文
3,521 篇 其他
563 篇 中文
208 篇 朝鲜文
37 篇 日文
4 篇 德文
1 篇 阿拉伯文
1 篇 法文
1 篇 斯洛文尼亚文
1 篇 土耳其文

检索条件"机构=Dept. of Electrical and Computer Engineering and Computer Science University of Cincinnati"

共 48413 条记录，以下是551-560 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：

Machine Learning Classification for Video Cleaning

Machine Learning Classification for Video Cleaning

引用

2023 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2023

作者： Yao, Brian Li, Wei University of Washington Department of Computer Science Seattle United States University of Victoria Dept. of Electrical and Computer Engineering Victoria Canada

ISBN: (纸本)9798350321524

Video data can often contain plenty of information that would be useful to analyze. However, most methods of collecting video data involve setting a camera to record for long periods of time, gathering mostly uninteresting data interspersed by sections of interesting events. Unlike past work in video cleaning which mostly deals with fixing incorrect labels, this paper explore ways to pick out the sections of interest from a mostly unlabeled video and only using small amounts of labeled data for training. Using only standard video features for generality, a variation of k-nearest neighbors is proposed and compared to other simple machine learning classifiers. These techniques are shown to be able to achieve up to 94% accuracy on the test data with as few as 100 training samples. © 2023 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

BSCIAM: A Blockchain based Secure Cloud Identity and Access Management Framework

BSCIAM: A Blockchain based Secure Cloud Identity and Access ...

引用

2024 IEEE International Students' Conference on electrical, Electronics and computer science, SCEECS 2024

作者： Das, Swatisipra Sahil, Mohammad Pandit, Naveen Kumar Priyadarshini, Rojalina Gochhayat, Sarada Prasad Fakir Mohan University Postgraduate Dept. of Computer Science Odisha India C.V. Raman Global University Dept. of Computer Science and Engineering Odisha India Indian Institute of Technology Jammu Dept. of Computer Science and Engineering J&K India

ISBN: (纸本)9798350348460

Cloud computing enables on-demand computation on remote servers and computers. Thanks to the adaptability and scalability of the infrastructure for data storage, processing, and management. To solve the security problems arising in cloud identity management techniques such as, dependency on a third-party token provider, leakage of user's details, single point of failure, etc., decentralized cloud identity management systems came into the picture. Blockchain is a decentralized database providing immutability and transparency to recorded transaction data. The current token-based decentralized cloud identity management systems have limitations, including the absence of data access management procedures and a lack of security features. This paper suggests a Blockchain based Secure Cloud Identity and Access Management (BSCIAM) model for secure identity and access management, utilizing encryption and key sharing techniques. The proposed model has been implemented using Ethereum smart contracts for token-based identity management. © 2024 IEEE.

关键词： access management blockchain cloud identity management

来源：评论

学校读者我要写书评

暂无评论

Optimizing Renewable Energy Management and Demand Response with Ant Colony Optimization: A Pathway to Enhanced Grid Stability and Efficiency

Optimizing Renewable Energy Management and Demand Response w...

引用

2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Islam, Riadul Kabir, Shaharier Shufian, Abu Rabbi, Md Shahiduzzaman Akteruzzaman, Md Lamar University Dept. of Electrical and Computer Engineering Texas United States American International University-Bangladesh Dept. of Electrical and Electronic Engineering Dhaka Bangladesh Dhaka Bangladesh

ISBN: (纸本)9798331541125

The integration of renewable energy sources into the power grid presents significant challenges due to their inherent variability and unpredictability. Efficient management of these sources and the effective implementation of demand response strategies are crucial for maintaining grid stability and optimizing energy usage. This study presents a comprehensive evaluation of the performance of Ant Colony Optimization (ACO) in optimizing microgrid operations compared to other modern algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA). The primary metrics of analysis include energy cost, renewable energy utilization, grid stability, and demand response effectiveness. Through a detailed dataset analysis and algorithmic implementation, the results indicate that ACO consistently outperforms its counterparts across all key performance indicators. ACO achieved the lowest energy cost, maximized renewable energy utilization, and maintained superior grid stability and demand response effectiveness. These findings highlight the potential of ACO as a robust optimization technique for enhancing the efficiency and sustainability of microgrid systems. The study underscores the importance of selecting appropriate algorithms to meet the complex and dynamic challenges of modern energy systems, promoting a transition towards greener and more reliable energy infrastructure. © 2025 IEEE.

关键词： Demand response

来源：评论

学校读者我要写书评

暂无评论

Multicarrier Waveforms for Moon-to-Earth RF Transmission 10

Multicarrier Waveforms for Moon-to-Earth RF Transmission

引用

10th IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2023

作者： Rahman, Talha Faizur Marojevic, Vuk Sacchi, Claudio Mississippi State University Dept. of Electrical and Computer Engineering Mississippi StateMS United States University of Trento Dept. of Information Engineering and Computer Science Trento Italy

ISBN: (纸本)9781665456906

More than 50 years after the last Apollo mission, the race to the Moon has started again. In the framework of new missions, it will be of paramount importance to establish a reliable communication link between the vehicles (or astronauts) present on the Moon's surface and an Earth station. Alternative choices consider radio-frequency (RF), optical, and hybrid optical-RF solutions. In this paper, we focus on the RF transmission case. Recent works evidenced how diversity is required to face multipath fading issues due to the reflection of electromagnetic rays on the Lunar surface. For this reason, suitable waveforms, which are robust against multi path distortion should be considered. In this work, we propose multicarrier Orthogonal Frequency Division Multiplexing (OFDM), Single-Carrier OFDM (SC-OFDM), and Constant-Envelope OFDM (CE-OFDM). The comparative results will be discussed in order to select the best solution to cope with the various tradeoffs between link performance, spectral efficiency, and computational complexity. © 2023 IEEE.

关键词： 5G mobile communication systems

来源：评论

学校读者我要写书评

暂无评论

Optimal Channel Selection for EEG-Based Enhanced Brain Robot Interface for Autonomous Wheelchair 12

Optimal Channel Selection for EEG-Based Enhanced Brain Robot...

引用

12th International Conference on Awareness science and Technology, iCAST 2023

作者： Sibli, Sabbir Ahmed Kabir, Raihan Jannat, Nuray Watanobe, Yutaka Islam, Md Rashedul Dept. of Computer Science and Engineering Fareast International University Banani Dhaka1213 Bangladesh Dept. of Computer Science and Engineering University of Aizu Aizuwakamatsu Fukushima Japan Dept. of Computer Science and Engineering BRAC University Dhaka1212 Bangladesh Dept. of Computer Science and Engineering University of Asia Pacific Dhaka1216 Bangladesh

ISBN: (纸本)9798350324693

Creating an autonomous wheelchair system based on EEG (electroencephalogram) signals is a fascinating and challenging concept. In non-invasive Brain robot Interface (BRI), scalp EEG signals acquired from the multiple channels come with different artifact types, majorly as an electrooculogram (EoG). Also, all the channels don't carry equally important information regarding the particular motor activities. The primary contribution of this paper is to denoise the EEG signal and then find the optimal channels to achieve the most informative EEG signals for the motor activity recognition. Thus, this research proposes a model where firstly t he E oG a rtifacts h ave b een removed from EEG signals with the regression method and other noises with Discrete Wavelet Transform (DWT). Secondly, It proposes a model of selecting optimal channels using a hybrid feature selection process, which includes a filter a nd w rapper method using sequential floating forward search (SFFS). Maximum Class Separability (MCS) and Support Vector Machine (SVM), both have been used for evaluating the channels. Then again SVM has been applied for classifying the motor activities by the signals recorded from the optimal channels. A dataset with four classes of human motor activities has been used for evaluating the whole proposed model. This proposed model shows the highest accuracy of 84.15% for the optimal channel set with Standard Deviation (STD) feature among other optimal channel sets of features. © 2023 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Atmospheric Turbulence Correction via Variational Deep Diffusion 6

Atmospheric Turbulence Correction via Variational Deep Diffu...

引用

6th IEEE International Conference on Multimedia Information Processing and Retrieval, MIPR 2023

作者： Wang, Xijun Lopez-Tapia, Santiago Katsaggelos, Aggelos K. Northwestern University Dept. of Computer Science EvanstonIL United States Northwestern University Dept. of Electrical and Computer Engineering EvanstonIL United States

ISBN: (纸本)9798350307818

Atmospheric Turbulence (AT) correction is a challenging restoration task as it consists of two distortions: geometric distortion and spatially variant blur. If left unaddressed, these distortions can significantly impact downstream vision tasks. Diffusion models have shown impressive accomplishments in photo-realistic image synthesis and beyond. In this paper, we propose a novel deep conditional diffusion model under a variational inference framework to solve the AT correction problem. We use this framework to improve performance by learning latent prior information from the input and degradation processes. We use the learned information to further condition the diffusion model. Experiments are conducted in a comprehensive synthetic AT dataset. We show that the proposed framework achieves good quantitative and qualitative results. © 2023 IEEE.

关键词： Atmospheric turbulence

来源：评论

学校读者我要写书评

暂无评论

LightNN: An Optimized Deep Learning Framework for Enhanced Fruit Classification

LightNN: An Optimized Deep Learning Framework for Enhanced F...

引用

2024 IEEE International Conference on Computing, Applications and Systems, COMPAS 2024

作者： Afroj, Maharin Jahan, Israt Islam, Md Polash Saifur Rahman, Md. Bangladesh University of Business and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Stockholm University Dept. of Computer and Systems Sciences Stockholm Sweden

ISBN: (纸本)9798331529765

The crucial field of fruit classification in computer vision and deep learning brings about breakthroughs that have broad applications in the retail and agricultural industries. By automating the identification and sorting of various fruit types, these technologies enhance efficiency, accuracy, and scalability, benefiting processes from farm production to market distribution. The integration of sophisticated algorithms and neural networks not only improves the speed and reliability of fruit classification but also offers the potential for real-time quality control and inventory management, revolutionizing traditional methods and paving the way for more innovative, data-driven approaches in these sectors. This study introduces LightNN, a novel and effective paradigm with a lightweight architecture that tackles the complex problems related to computational efficiency. Combining a small classifier with a simplified feature extractor, LightNN achieves the ideal balance between simplicity and accuracy. The feature extractor is capable of extracting hierarchical features from RGB images by using convolutional layers with ReLU activations and max-pooling procedures. The flattened output is then processed by the classifier, which consists of fully connected layers with ReLU activations and dropout regularisation. Remarkably, LightNN, with just 298,835 parameters, manages to get a respectable 96.37% test accuracy in fruit categorization tasks. The results highlight LightNN's promise as an effective and efficient fruit classifying method, particularly in situations with constrained computational resources. © 2024 IEEE.

关键词： Fruits

来源：评论

学校读者我要写书评

暂无评论

Protecting Battery Health During Charge and Discharge for Electric Vehicles

Protecting Battery Health During Charge and Discharge for El...

引用

2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Anonto, Hasanur Zaman Hossain Emon, Md Mukter Nandi, Anup Islam, Sashyni Hossain, Md Ismail Shufian, Abu American International University-Bangladesh Dept. of Electrical and Electronic Engineering Dhaka Bangladesh Dhaka Bangladesh Lamar University Dept. of Electrical and Computer Engineering TX United States

ISBN: (纸本)9798331541125

Lithium-ion (Li-ion) batteries are pivotal to electric vehicles performance, efficiency, and sustainability (EVs), offering high energy density, lightweight design, and the ability to endure hundreds of charge-discharge cycles. However, they are susceptible to suboptimal operating conditions, including overcharging, under-discharging, and exposure to extreme temperatures. These can significantly degrade battery capacity, shorten lifespan, and pose safety hazards such as thermal runaway. This paper investigates advanced battery management systems (BMS) and protection mechanisms to mitigate these risks. Through optimized charge/discharge strategies, real-time monitoring, and precise temperature regulation within safe operating limits (15°C to 45°C), the proposed methods demonstrate the potential to reduce battery degradation by up to 30% and extend overall battery life by 20%. Additionally, integrating solid-state battery technology is explored as a promising solution to enhance battery safety, energy density, and reliability. These advancements improve the long-term performance of EV batteries and contribute to the broader goal of making electric transportation systems safer, more sustainable, and more efficient for future mobility. © 2025 IEEE.

关键词： Solid-State Batteries

来源：评论

学校读者我要写书评

暂无评论

Optimizing Photovoltaic System Efficiency: A Comparative Study of RNN-based Controller and Incremental Conductance in MPPT 52

Optimizing Photovoltaic System Efficiency: A Comparative Stu...

引用

52nd IEEE Photovoltaic Specialist Conference, PVSC 2024

作者： Soyoye, Babatunde D. Bhattacharya, Indranil Vinolisha, Mary Banik, Trapa Tennessee Tech University Electrical and Computer Engineering dept. CookevilleTN38505 United States Tennessee Tech University Antony Dhason Electrical and Computer Engineering dept. CookevilleTN38505 United States

ISBN: (纸本)9781665464260

In this study, a Recurrent Neural Network (RNN)- based PV controller is thoroughly examined and compared with conventional Incremental Conductance techniques for Maximum Power Point Tracking (MPPT). The study emphasizes the improved responsiveness and efficiency of the RNN controller and focuses on the dynamic adaptation of PV systems to changing environmental conditions. In this study, the better performance of the RNN controller in monitoring the maximum power point, its fast convergence time, and its stability under various environmental conditions are demonstrated by comprehensive simulations and comparative studies. According to the results, using cutting-edge machine learning methods, such as RNNs, may greatly increase PV systems' operational effectiveness, highlighting their potential to optimize renewable energy systems. This study offers insights that advance the realm of renewable energy technologies. © 2024 IEEE.

关键词： DC-DC Boost converter Incremental conductance Machine learning Maximum Power Point Tracking (MPPT) Photovoltaic systems Recurrent Neural Network

来源：评论

学校读者我要写书评

暂无评论

Optimizing EV Charging Infrastructure through Behavioral Analysis, Smart Charging, and V2G Integration

Optimizing EV Charging Infrastructure through Behavioral Ana...

引用

2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Hossain, Md Ismail Anonto, Hasanur Zaman Hossain Emon, Md Mukter Nandi, Anup Shahriyar, Azad Shufian, Abu American International University-Bangladesh Dept. of Electrical and Electronic Engineering Dhaka Bangladesh Dhaka Bangladesh Lamar University Dept. of Electrical and Computer Engineering TX United States

ISBN: (纸本)9798331541125

The rapid adoption of electric vehicles (EVs) underscores the pressing need for optimized charging infrastructure to meet growing demands. This study investigates the integration of behavioral analysis, innovative charging strategies, and vehicle-to-grid (V2G) technology to improve EV infrastructure efficiency and grid stability. This research identifies key factors that influence charging demand and usage by examining user-specific charging patterns, including differences between private and fleet users. Smart charging and dynamic pricing models are explored to alleviate peak load stress, while V2G solutions enhance energy distribution during demand fluctuations. The findings emphasize the significance of flexible infrastructure planning, which includes Level 1, Level 2, and DC fast chargers strategically deployed to cater to diverse EV user needs. This approach offers a pathway to a sustainable, scalable charging ecosystem, promoting both user convenience and grid resilience. © 2025 IEEE.

关键词： Charging stations

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 << < 52 53 54 55 56 57 58 59 60 61 > >>

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：