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

118,601 篇 会议
54,350 篇 期刊文献
961 册 图书

馆藏范围

173,911 篇 电子文献
3 种 纸本馆藏

日期分布

学科分类号

98,067 篇 工学
- 48,716 篇 计算机科学与技术...
- 38,320 篇 软件工程
- 22,765 篇 信息与通信工程
- 22,052 篇 电子科学与技术（可...
- 21,706 篇 电气工程
- 17,242 篇 控制科学与工程
- 9,690 篇 光学工程
- 8,699 篇 生物工程
- 7,487 篇 机械工程
- 7,087 篇 材料科学与工程（可...
- 7,016 篇 化学工程与技术
- 6,920 篇 生物医学工程（可授...
- 6,812 篇 仪器科学与技术
- 6,694 篇 动力工程及工程热...
- 3,021 篇 力学（可授工学、理...
- 2,739 篇 交通运输工程
- 2,399 篇 建筑学
59,602 篇 理学
- 26,526 篇 数学
- 25,452 篇 物理学
- 9,747 篇 生物学
- 8,950 篇 统计学（可授理学、...
- 7,460 篇 化学
- 7,415 篇 系统科学
17,252 篇 管理学
- 11,607 篇 管理科学与工程(可...
- 6,119 篇 图书情报与档案管...
- 5,733 篇 工商管理
5,847 篇 医学
- 4,855 篇 临床医学
- 4,176 篇 基础医学(可授医学...
- 2,674 篇 药学(可授医学、理...
3,045 篇 法学
- 2,637 篇 社会学
2,276 篇 经济学
1,350 篇 教育学
1,235 篇 农学
630 篇 文学
366 篇 军事学
170 篇 艺术学
23 篇 哲学
16 篇 历史学

主题

6,902 篇 computer science
3,332 篇 computational mo...
2,472 篇 bandwidth
2,383 篇 feature extracti...
2,333 篇 control systems
2,133 篇 accuracy
2,080 篇 optimization
2,044 篇 training
1,952 篇 computer archite...
1,940 篇 costs
1,905 篇 hardware
1,878 篇 mathematical mod...
1,867 篇 testing
1,800 篇 switches
1,785 篇 delay
1,779 篇 machine learning
1,777 篇 robustness
1,729 篇 wireless sensor ...
1,649 篇 neural networks
1,619 篇 application soft...

机构

1,461 篇 department of el...
1,248 篇 department of el...
566 篇 school of optica...
478 篇 department of el...
465 篇 department of el...
444 篇 school of electr...
422 篇 school of electr...
406 篇 faculty of elect...
379 篇 school of electr...
329 篇 department of el...
319 篇 school of automa...
315 篇 faculty of elect...
304 篇 department of el...
283 篇 department of el...
275 篇 school of electr...
212 篇 department of el...
205 篇 school of electr...
204 篇 school of electr...
193 篇 school of comput...
192 篇 ieee

作者

345 篇 niyato dusit
201 篇 han zhu
101 篇 g. tonelli
99 篇 d. barney
93 篇 c. hensel
92 篇 l. valencia palo...
90 篇 t. liu
88 篇 a. garcia-bellid...
88 篇 a. steen
87 篇 a. babaev
87 篇 n. cartiglia
86 篇 k.g. shin
85 篇 v. karjavine
85 篇 seung-ki sul
83 篇 y. chen
81 篇 n. colino
79 篇 f. moortgat
78 篇 w. busza
76 篇 h. wang
74 篇 f. buehrer

语言

152,879 篇 英文
18,850 篇 其他
2,138 篇 中文
78 篇 日文
37 篇 朝鲜文
27 篇 德文
16 篇 法文
9 篇 斯洛文尼亚文
5 篇 俄文
4 篇 阿拉伯文
3 篇 西班牙文
2 篇 捷克文
2 篇 葡萄牙文
2 篇 土耳其文
1 篇 意大利文
1 篇 荷兰文
1 篇 波兰文

检索条件"机构=Electrical and Computer Engineering and Computer Science"

共 173912 条记录，以下是4731-4740 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：

Insole Design and Optimization Processes for Gait Analysis

Insole Design and Optimization Processes for Gait Analysis

引用

2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Orozco Villanueva, Kevin Alejandro Richter, Miguel Villa, Carlos Martinez-Villasenor, Lourdes Ponce, Hiram Barrera-Animas, Ari Yair Universidad Panamericana Faculty of Engineering Mexico City Mexico Massachusetts Institute of Technology Electrical Engineering and Computer Science Boston United States

ISBN: (纸本)9781665430654

Gait analysis is becoming increasingly central in various fields such as biomechanics, medicine, and sports. This complex study assesses how individuals walk, weighing in on aspects like bone alignment, joint range of motion, and neuro-muscular activity. Its profound importance emanates from its capability to identify potential walking anomalies at an early stage, which can offset the need for invasive medical interventions and offer valuable insights for clinicians to make well-informed decisions. Inspiration for this in-depth gait analysis research was sourced from previous attempts that employed tools like step mats and cameras to track and analyze movement. Several design imperatives were consolidated within this framework, including the vital need of user safety, assuring comfort throughout usage, preserving system stability, and the undoubtedly significant feature of keeping the insole lightweight. These priorities were not merely for user comfort but were essential for the fidelity of the data being captured. In this paper, it is described the design and optimization processes of an insole for gait analysis following an agile methodology which involves the following stages: requirements, design, implementation and testing. This study delves deeply into the challenges of designing, implementing, and optimizing instrumented insoles for gait analysis. The requirements were successfully achieved by creating a 3mm-thick, flexible insole using TPU 95 material through 3D printing. This insole effectively encapsulates electronic components, ensuring comfort, durability, and safety. © 2023 IEEE.

关键词： Gait analysis insole unobtrusive wearable

来源：评论

学校读者我要写书评

暂无评论

Temporal Graph Representation Learning via Maximal Cliques

Temporal Graph Representation Learning via Maximal Cliques

引用

2022 IEEE International Conference on Big Data, Big Data 2022

作者： Khoshraftar, Shima An, Aijun Babanejad, Nastaran York University Electrical Engineering and Computer Science Department Toronto Canada

ISBN: (纸本)9781665480451

Graph Neural Networks (GNNs) have been proposed to learn graph representations for various graph mining tasks such as link prediction and node classification. These methods aggregate information from neighbors of a node to generate the node representation vector. Temporal GNN models consider the temporal and neighborhood information of nodes. However, few temporal GNN methods consider network substructures such as triads and cliques. In this paper, we present a temporal GNN-based method that generates node embeddings by aggregating neighbors of a node that exist in the maximal cliques of the graph containing the node. The reason for considering neighbors that form a maximal clique with the target node is that nodes in a maximal clique are highly connected to each other and most likely share similar characteristics. In addition, we consider the time dependency of nodes by generating temporal walks on the cliques such that in these walks the time order of the nodes is respected. The node embedding is based on the aggregation of the node's temporal walks. Our experiments on seven datasets show the effectiveness of our method in both link prediction and node classification tasks. Furthermore, our method is faster than other baselines we evaluate. © 2022 IEEE.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Generative Adversarial Network with Adaptive Synthesis for Brain-computer Interfaces in Motor Imagery Classification

Generative Adversarial Network with Adaptive Synthesis for B...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zhou, Qiaoli Ye, Xiyuan Li, Shurui Zhao, Yi Du, Qiang Ke, Li School of Computer Science Shenyang Aerospace University Liaoning Shenyang110136 China School of Electrical Engineering Shenyang University of Technology Liaoning Shenyang110870 China

ISBN: (纸本)9798350368741

Motor Imagery (MI) is essential in Brain-computer Interfaces (BCIs), highlighting the central role of electroencephalography (EEG) in this technology. However, the amount of raw EEG data is often limited. Raw EEG data contains significant noise caused by individual and task-specific differences. These complications often necessitate the removal of noise, making it crucial to develop robust models capable of maintaining performance. To achieve this, synthetic data is essential to obtain cleaner signals. This paper presents a novel a novel contrastive diffusion model to adaptive synthesize clean signals for Motor Imagery Classification (CDASC-MI), achieved through three components: Clean Signal Extractor(CSE) for clean signal feature learning, Adapative Noise Extractor(ANE) for adaptively extracting subject noise and task noise, and Contrastive Module for further separating noise to obtain cleaner signals. Specifically, we first proposed the novel Cell-UNET in CSE, which is an architecture with progressive learning capabilities to effectively capture subtle changes in EEG signals. Additionally, ANE incorporates a novel Subject Feature Learning Network(SFLNet) and Cross-Domain Electrode Attention Network (CDANet). SFLNet and CDANet dynamically capturing variation subject noise and task noise. Ultimately, a Contrastive Module is designed to use contrastive learning during the denoising process to amplify the differences between clean signals and noise, ensuring robust denoising and clearer feature representation. According to experimental results from two public datasets, the proposed method achieved superior accuracies of 96.19% and 89.19%, outperforming existing approaches. It highlights its potential as a powerful method for augmenting EEG datasets and improving the accuracy and highlight its broad application values. © 2025 IEEE.

关键词： DDPM Deep Learning Domain-attention EEG

来源：评论

学校读者我要写书评

暂无评论

SymPyCAP: Software for symbolic analysis of electric circuit 10

SymPyCAP: Software for symbolic analysis of electric circuit

引用

10th International Conference on electrical, Electronic and Computing engineering, IcETRAN 2023

作者： Dodović, Matija Stanković, Katarina Ilić, Nikola Bakić, Jelena University of Belgrade School of Electrical Engineering The Department of Computer Science and Information Technology Belgrade Serbia University of Melbourne Faculty of Science Melbourne Australia High School of Electrical Engineering Belgrade Serbia

ISBN: (纸本)9798350307115

The aim of this paper is to present SymPyCAP software for the symbolic analysis of linear time-invariant electric circuits. This software is written in Python and uses modified nodal analysis to solve equations in Laplace Transform domain and in Phasor Transform domain. How SymPyCAP solves electric circuits is demonstrated using several representative electric circuits. © 2023 IEEE.

关键词： Laplace transforms

来源：评论

学校读者我要写书评

暂无评论

Automated Brain Tumor Detection Using Soft Computing-Based Segmentation Technique 3

Automated Brain Tumor Detection Using Soft Computing-Based S...

引用

3rd International Conference on Computing and Information Technology, ICCIT 2023

作者： Zubair, Muhammad Umair, Muhammad Owais, Muhammad University of Central Punjab Faculty of Information Technology & Computer Science Lahore Pakistan Khalifa University Kucars C2PS Dept of Electrical Engineering & Computer Science United Arab Emirates

ISBN: (纸本)9798350321487

Development and growth of abnormal cells within the brain results in brain tumor. In this study, a novel segmentation methodology is proposed for the segmentation of tumor. The proposed model consists of two phases. In the first phase, the brain CT image from the medical database is pre-processed to remove artifacts and noise. For Image segmentation, a Hierarchical Self Organizing Map (HSOM) is used that provides promising segmentation results. The conformist Self Organizing Map (SOM), which was used to categorize the picture row by row, is extended by the HSOM. Thus, the HSOM with vector quantization speeds up calculation at this lowest level of the weight vector, where there are more tumor pixels. The proposed automated system is tested on Kaggle (online available) database and achieves an accuracy of 98.94%. © 2023 IEEE.

关键词： Self organizing maps

来源：评论

学校读者我要写书评

暂无评论

State-of-Charge Prediction of Degrading Li-ion Batteries Using an Adaptive Machine Learning Approach

State-of-Charge Prediction of Degrading Li-ion Batteries Usi...

引用

2022 IEEE Power and Energy Society General Meeting, PESGM 2022

作者： Babaeiyazdi, Iman Rezaei-Zare, Afshin Shokrzadeh, Shahab York University Department of Electrical Engineering and Computer Science Toronto Canada

ISBN: (数字)9781665408233

ISBN: (纸本)9781665408233

State of charge (SOC) estimation of degrading batteries is important for battery energy storage systems (BESS) employed in power system applications and electric vehicles. This paper aims to propose a comparative analysis for data-driven models such as linear regression (LR), support vector regression (SVR), random forest (RF), and Gaussian process regression (GPR) to estimate the battery SOC at various temperatures and loading levels considering the state of health (SOH) of the battery. The historical data in which the cells are degraded from SOH of 100% to 60% are employed to extract the correlated features with the SOC. The models are retrained and adaptively updated based on the new SOH and prepared to estimate the SOC at the current SOH. The results demonstrate that GPR and RF models have the best performance. The mean absolute error of less than 0.0223 and 0.0204 have been achieved for RF and GPR, respectively. © 2022 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

When is Automated Feedback a Barrier to Timely Feedback? 129

When is Automated Feedback a Barrier to Timely Feedback?

引用

129th ASEE Annual Conference and Exposition: Excellence Through Diversity, ASEE 2022

作者： Deorio, Andrew Keefer, Christina Department of Electrical Engineering and Computer Science University of Michigan United States

Computing programs have seen a substantial enrollment increases in recent years. One of the challenges brought by rising enrollments is long wait times for students to receive help in office hours. Schools tackling aggressive scaling have turned to peer teaching and automated feedback mechanisms to aid students seeking help. We examine the relationship between the demand for peer teaching and different automated feedback mechanisms. More specifically, in response to a fixed per capita supply of office hours, do different types of autograder feedback drive different levels of demand for office hours? Our study examines 3 years of data from 17 computing courses at a large, public university comprising 4 different types of autograder feedback. We collected 105941 unique encounters between students and peer teachers in office hours. Each encounter includes information about the student and staff member involved, the amount of time that the student waited, and the amount of time that the student was helped. Our results suggest that some automated feedback mechanisms used to provide timely feedback are counter-intuitively associated with greater demand for office hours and longer wait times for students to receive feedback. In particular, more opaque automated feedback was associated with up to 57% longer wait times for office hours compared to more transparent automated feedback. A course that switched from opaque feedback to more detailed feedback decreased wait times by 24%. These results can help instructors leverage automated feedback while ensuring timely access to peer teachers in office hours. © American Society for engineering Education, 2022.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Price Spike Classification and Regression Using A Hybrid Oversampling Method

Price Spike Classification and Regression Using A Hybrid Ove...

引用

2022 North American Power Symposium, NAPS 2022

作者： Zhang, Chenxu Gong, Lin Peng, Yehong Fu, Yong Mississippi State University Department of Electrical and Computer Engineering StarkvilleMS United States Jackson State University Department of Electrical & Computer Engineering and Computer Science JacksonMS United States

ISBN: (纸本)9781665499217

Price spikes are types of electricity prices that are much higher than normal electricity prices. However, due to low occurrence, price spikes are hard to be predicted by normal price forecast methods, which are designed to model patterns from the dataset with massive normal price cases. To facilitate price spike classification and regression, in this paper, a hybrid oversampling method is proposed to increase the number of price spike cases. As electricity prices are time series data, to enable that the synthetic price spike cases have the similar structure as the real ones, the enhanced structure preserving oversampling technique is applied to conserve the temporal relationships. Also, the synthetic minority oversampling method for regression is utilized to ensure the authenticity of the oversampled price spike values. Numerous case studies are used to evaluate the effectiveness of the proposed hybrid oversampling method, and the promising results demonstrate the capability of the proposed method to improve price spike classification and regression accuracy. © 2022 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Estimating Risk Levels and Epidemiology of Diabetic Retinopathy using Transfer Learning 3

Estimating Risk Levels and Epidemiology of Diabetic Retinopa...

引用

3rd International Conference on Secure Cyber Computing and Communications, ICSCCC 2023

作者： Biswas, Ankur Banik, Rita Tripura Institute of Technology Computer Science & Engineering Tripura Agartala India Icfai University Electrical Engineering Tripura West Tripura India

ISBN: (纸本)9798350300710

Diabetic retinopathy is one among the visible microvascular effects of diabetes that may affect the retina of the human eye, and their images are now employed for manual disease evaluation and conclusion. Professional graders use feature-based evaluation criteria when using diagnostic methods for diabetic retinopathy (DR). Modern deep learning (DL) methods, on the other hand, are engrossed in end-to-end training and rely on image domain data labeling. The majority of these prognosis require a large training data to provide a straight categorization grade. This research is an attempt to accelerate the initial screening for DR on limited data in order to address the future needs of the diabetic community. In this study, we analyze the DL-based system trained on big data that can be further applied on smaller samples of retina image for screening of DR with the goal of supporting variable grades and track its progression. We developed and verified accurate classification models based on transfer learning to estimate the risk levels and epidemiology of DR using publicly available datasets, allowing for the prompt identification of DR. We applied data augmentation using Generative Adversarial Network to balance the dataset. For the grading of DR through multi-class (5-class) classification with augmented data, the precision varies from 0.40 to 0.97 on accessible datasets. The accuracy for detecting the presence of DR via binary classification ranges from 0.94 to 0.98, further adds to the model's efficacy in diagnosing diabetic retinopathy. © 2023 IEEE.

关键词： Grading

来源：评论

学校读者我要写书评

暂无评论

Uncertainty Estimation for Gradient Boosting Models based on Gaussian Graph Model and Natural Gradient 3

Uncertainty Estimation for Gradient Boosting Models based on...

引用

3rd International Conference on Machine Learning and computer Application, ICMLCA 2022

作者： Chen, Muyi Wang, Daling College of Computer Science and Engineering Northeastern University Shenyang China School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China

ISBN: (纸本)9781510664814

We study the multi-output probability regression prediction and uncertainty quantification problem in multi-output regression prediction with gradient boosting models, and propose an uncertainty estimation method based on Gaussian Graph Model (GMM) constraint and natural gradient. Under the assumption of Gaussian distribution, we employ GMM to model the conditional independence relationship of the outputs, and propose a mixed parameterization to represent the subfamily of Gaussian distributions defined by the graph model. We set this mixed parameters as the learning target of the gradient boosting model, and use natural gradient in Riemann space that based on Fisher information matrix (FIM) instead of the vanilla gradient to be the steepest descent direction. The formula to compute FIM and natural gradient for the subfamily defined by GMM is deduced. Experiments show that the proposed method is able to incorporate the priors on the outputs to optimize the search space, therefore, lead to better uncertainty estimation results on multi-output regression for gradient boosting models. © 2023 SPIE.

关键词： Fisher information matrix

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 << < 470 471 472 473 474 475 476 477 478 479 > >>

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：