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

758 篇 会议
3 册 图书
2 篇 期刊文献

馆藏范围

763 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

656 篇 工学
- 535 篇 计算机科学与技术...
- 466 篇 软件工程
- 246 篇 信息与通信工程
- 147 篇 生物工程
- 114 篇 光学工程
- 93 篇 控制科学与工程
- 92 篇 电气工程
- 91 篇 电子科学与技术（可...
- 76 篇 生物医学工程（可授...
- 54 篇 化学工程与技术
- 40 篇 机械工程
- 34 篇 仪器科学与技术
- 34 篇 材料科学与工程（可...
- 30 篇 安全科学与工程
- 28 篇 动力工程及工程热...
- 25 篇 交通运输工程
- 24 篇 土木工程
439 篇 理学
- 203 篇 数学
- 159 篇 物理学
- 153 篇 生物学
- 71 篇 统计学（可授理学、...
- 66 篇 化学
- 34 篇 系统科学
199 篇 管理学
- 123 篇 图书情报与档案管...
- 98 篇 管理科学与工程(可...
- 39 篇 工商管理
52 篇 医学
- 49 篇 基础医学(可授医学...
- 49 篇 临床医学
- 36 篇 药学(可授医学、理...
29 篇 法学
- 26 篇 社会学
15 篇 经济学
15 篇 农学
14 篇 教育学
2 篇 军事学

主题

23 篇 deep learning
19 篇 machine learning
16 篇 support vector m...
15 篇 feature extracti...
14 篇 computer vision
11 篇 convolution
11 篇 natural language...
11 篇 sentiment analys...
10 篇 internet of thin...
10 篇 object detection
10 篇 big data
10 篇 semantics
10 篇 convolutional ne...
9 篇 natural language...
7 篇 signal processin...
7 篇 visualization
6 篇 signal detection
6 篇 deep neural netw...
6 篇 graphics process...
6 篇 neural networks

机构

7 篇 key laboratory o...
7 篇 school of inform...
6 篇 school of comput...
6 篇 xinjiang key lab...
6 篇 school of inform...
6 篇 xinjiang key lab...
6 篇 key laboratory o...
4 篇 nss college of e...
4 篇 school of comput...
4 篇 college of infor...
4 篇 school of contro...
3 篇 school of comput...
3 篇 department of co...
3 篇 college of compu...
3 篇 college of intel...
3 篇 guangdong polyte...
3 篇 school of comput...
3 篇 school of comput...
3 篇 academy for engi...
2 篇 hefei university...

作者

10 篇 hamdulla askar
6 篇 ablimit mijit
5 篇 gao yanxia
5 篇 liu yiwen
4 篇 shi yuanquan
4 篇 xiao jianhua
3 篇 faisal rehman
3 篇 wang chao
3 篇 xiao hongbo
3 篇 sharif hanan
3 篇 peng xiaoning
3 篇 rehman faisal
3 篇 chen xi
3 篇 mala c.
3 篇 shi zhen-gang
3 篇 li chao
3 篇 jiang huiming
3 篇 yuan jing
3 篇 li jing
3 篇 zhao qian

语言

749 篇 英文
14 篇 其他
1 篇 中文

检索条件"任意字段=2022 3rd International Conference on Signal Processing and Computer Science, SPCS 2022"

共 763 条记录，以下是491-500 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：

A Comprehensive Review of Epileptic Seizure Prediction using Medical Internet of Things 3

A Comprehensive Review of Epileptic Seizure Prediction using...

引用

3rd international conference on Power, Energy, Control and Transmission Systems, ICPECTS 2022

作者： Hema, P. Vanithamani, R. Jai Shriram Engineering College Department of Electrical &electronics Engineering Tiruppur India School of Engineering Avinashilingam Institute for Home Science and Higher Education for Women Department of Biomedical Instrumentation Engineering Coimbatore India

ISBN: (纸本)9781665462754

A neurological disorder in the nervous system is a structural, biochemical or electrical abnormality in the brain or spinal cord. Epilepsy is the most common disorder among various neurological disorders, and recurrent epileptic seizures characterize it. A seizure is a period of symptoms due to excessive neuronal activity in an abnormal manner. Seizures are either due to provoked conditions like blood sugar, brain infections, and fever or unprovoked conditions like stress or sleeplessness. The reliable prediction of epileptic seizures involves pre-processing of signals from EEG sensors by enhancing the signal to noise ratio. By recording the brain's electrical activity using electrodes attached to the brain, epilepsy has been diagnosed. Nowadays, IoT based epilepsy detection is the most common real-time diagnostic procedure for detecting abnormalities in the brain using EEG sensor data. The involvement of sensors and IoT in medical healthcare research implementations can improve the diagnosis and detection of brain abnormalities which results in the enhancement of smart healthcare research. The high-end device utilization affects high energy consumption, leading to prolonged diagnostic decisions. The signal quality analysis process lags due to less concentrated research in classification and detection. The delay and error rate has to be reduced by concentrating more on energy management. An energy-efficient epileptic seizure prediction framework using EEG sensor data has been proposed to resolve and reduce such issues. The energy utilization of the epileptic seizure prediction using the Medical Internet of Things (MIoT) will be optimized. The trade-offs between accuracy, reliability, and delay of the effective energy-optimized epileptic seizure prediction using the MIoT framework will be enhanced. © 2022 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Evaluating and Improving RoSELS for Road Surface Extraction from 3D Automotive LiDAR Point Cloud Sequences 1

引用

3rd international conference on Deep Learning Theory and Applications, DeLTA 2022

作者： Katkoria, Dhvani Sreevalsan-Nair, Jaya Graphics-Visualization-Computing Lab IIIT Bangalore 26/C Electronics City Karnataka 560100 India

ISBN: (数字)9783031373176

ISBN: (纸本)9783031373169

Navigable space determination is a difficult problem encountered in robotics and intelligent vehicle technology and it requires integrated solutions using advances in computer vision and computational geometry. The conventional data processing workflow uses semantic segmentation to identify road points from three-dimensional (3D) automotive LiDAR point clouds, which have to be extended to determine its boundary points. The boundary points are critical in getting an initial coarse extraction of its surface. Hence, to filter the curb or edge points from the road points, the semantic segmentation results are post-processed. The road surface is determined by the entire trajectory information, which is captured as a sequence of LiDAR point clouds. For the entire road surface extraction, we use an automated system, RoSELS (Road Surface Extraction for LiDAR point cloud Sequence) that works at different scales, i.e., at the scale of a point, a point cloud, and the sequence of point clouds. In this paper, we evaluate the algorithms used in RoSELS, namely, the Gaussian Mixture Model for curb detection and ResNet-50 for transfer learning in frame classification. We evaluate the quality of the mesh extracted using RoSELS, which is intended for straight-road geometry. Here, we also show how the initial extracted surface can be further post-processed to extend RoSELS for curved roads. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Vehicles

来源：评论

学校读者我要写书评

暂无评论

Sentiment Analysis on Drug Reviews Using Diverse Classification Techniques 3

Sentiment Analysis on Drug Reviews Using Diverse Classificat...

引用

3rd international conference on Communication, Computing and Industry 4.0, C2I4 2022

作者： Duraisamy, Premkumar Natarajan, Yuvaraj Preethaa, K.R.Sri Mouthami, K. KPR Institute of Engineering and Technology Department of Artificial Intelligence and Data Science Coimbatore India KPR Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Research Professor Intelligent Construction Automation Center Kyungpook National University Deagu Korea Republic of

ISBN: (纸本)9781665474979

Free text reviews are abundantly distributed over the internet among the standard population of the world. Although online doctors were consulted during the pandemic, many drugs are taken without prescription by ordinary people. Reviews are distributed about the medicines through online feeds, posts and blogs, which are merely helpful in identifying the side effects and their adverse reactions in combination with another drug or standalone adverse reactions. Spelling mistakes, jargon and short names are normalized throughout the medical terminologies using Natural language processing (NLP) and RxNorm from the reviews extracted from these sources. The concept of Bidirectional Encoder Representations from Transformers (BERT) is used to mine the association rules for the drug interactions when used in conjugation with another drug, and the idea of Adaptive Fuzzy logic neural networks is used to validate the results of association rules derived from the BERT. Inconsistencies identified by the regulations generated were rejected efficiently by the Support vector machines (SVM), Radial Basis Function (RBF)and the system shows 60.11 percentage of accuracy with 10 cross-fold validation, whereas the results are equivalent to the accuracy obtained using SVM with RBF kernel. The data set is reduced from its dimension using Linear discriminant analysis (LDA) by applying the mining process and BERT on two drugs, namely 'Azithromycin' in conjugation with Buprenorphine has Type 'A' side effects, and Prozac in conjugation with Metronidazole shows different side effects. Deplin and Zoloft give very positive symptoms and are independent of dosage interactions. © 2022 IEEE.

关键词： Bidirectional Encoder Representations from Transformers (BERT) Linear discriminant analysis (LDA) Radial Basis Function (RBF) Support vector machines (SVM)

来源：评论

学校读者我要写书评

暂无评论

Effectiveness Analysis of the Mel spectrum features of AE signals in the detection of partial discharge faults 3

Effectiveness Analysis of the Mel spectrum features of AE si...

引用

3rd international conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2022

作者： Lu, Lian Tao, Wanning Liu, Guangyu Xiao, Hui Li, Xuefeng College of Electronic and Information Engineering Tongji University Shanghai China College of Electronic and Information Engineering Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China

ISBN: (纸本)9781665492812

Acoustic emission (AE) technologies have been widely used in the detection of partial discharge (PD) faults. Currently, obtaining the time-frequency spectrum of a signal by short-time Fourier transform or wavelet transform and then extracting the practical features for fault identification has received increasing attention. This is because the time-frequency spectrum holds a wider variety of intrinsic characteristics of the signal source, which helps enhance the understanding of faults and improve identification accuracy. A high-resolution linear time-frequency analysis method can provide a more detailed signal characterization capability for processing time-frequency spectra. However, the bandwidth of AE signals is usually up to several hundreds of kHz, which means the significant correlation coefficients between spectra tend to generate high redundancy characteristics. This study proposes a method to optimize the time-frequency spectrum density distribution based on the Filter Banks features. The method achieves highly desirable results by converting the AE signal into a Mel spectrum and using ResNet50 to extract spectral features for training and fault type classification. The research results promote the development of AE detection technology applications and, in some ways, provide a valuable reference for machine learning-oriented sound signal processing methods. © 2022 IEEE.

关键词： Gas-insulated switchgear partial discharge ResNet50 time-frequency spectrum

来源：评论

学校读者我要写书评

暂无评论

IoT-based Battery Management System for E-Vehicles 3

IoT-based Battery Management System for E-Vehicles

引用

3rd international conference on Smart Electronics and Communication, ICOSEC 2022

作者： Krishnakumar, S. Kumar, Akhilesh Selvarani, N. Satish, G. Ramanchandan, Radha Hemavathi Sivaramkrishnan, M. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Electrical and Electronics Engineering TamilNadu Chennai600062 India Guru Nanak Dev Dseu Rohini Campus Department of Electrical Engineering Delhi110089 India Psna College of Engineering and Technology Department of Electrical and Electronics Engineering TamilNadu Dindigul624622 India Sree Dattha Institute of Engineering and Science Department of Electrical and Electronics Engineering Telangana Sheriguda Ibrahimpatnam Hyderabad501510 India Shambhunath Institute of Engineering and Technology Department of Computer Science & Engineering Uttar PradeshJhalwa Prayagraj211015 India Yanbu Industrial College Alnahdah Electrical and Electronics Engineering Technology Department Al-Nahdah Yanbu46452 Saudi Arabia CSIR-Madras Complex Battery Division Tamil Nadu Chennai600 113 India 6bAcademy of Scientific & Innovative Research Uttar Pradesh Ghaziabad201 002 India Karpagam College of Engineering Department of Eee India

ISBN: (数字)9781665497640

ISBN: (纸本)9781665497640

In today's modern world electric vehicles are in trend for transportation purposes and it replaces traditional transportation, by making a pollution-free environment. In electric vehicles, different types of batteries like Lithium batteries, Lead-acid batteries, Nickel-Metal batteries, and Solid-state batteries are used. Of these types of batteries, the most preferable is the Lithium battery. Because of its high energy per unit mass and most efficient than other batteries and it can be recycled. In this study, a battery management system is proposed using the Internet of Things. This system comprises of sensors like temperature, voltage, and current which send the signal to the microcontroller and send the data to the cloud-like ThingSpeak. When the data goes to a high level, the alert mail will be sent by ThingSpeak and the place can be located by using the Global Positioning System. The perspective of this paper is to maintain the batteries in the electric vehicle to alert about the performance of the battery. © 2022 IEEE.

关键词： Global positioning system

来源：评论

学校读者我要写书评

暂无评论

Functional simulation of real-time quantum control software 3

Functional simulation of real-time quantum control software

引用

3rd IEEE international conference on Quantum Computing and Engineering (QCE)

作者： Riesebos, Leon Brown, Kenneth R. Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA

ISBN: (数字)9781665491136

ISBN: (纸本)9781665491136

Modern quantum computers rely heavily on real-time control systems for operation. Software for these systems is becoming increasingly more complex due to the demand for more features and more real-time devices to control. Unfortunately, testing real-time control software is often a complex process, and existing simulation software is not usable or practical for software testing. For this purpose, we implemented an interactive simulator that simulates signals at the application programming interface level. We show that our simulation infrastructure simulates kernels 6.9 times faster on average compared to execution on hardware, while the position of the timeline cursor is simulated with an average accuracy of 97.9% when choosing the appropriate configuration.

关键词： real-time control software signal simulation software testing quantum computing

来源：评论

学校读者我要写书评

暂无评论

computer intelligent prediction model of resisting dust storms based on entropy weight method and time series 3

Computer intelligent prediction model of resisting dust stor...

引用

3rd international conference on computers, Information processing and Advanced Education, CIPAE 2022

作者： Yitong, Liu Lutong, Zhao Kai, Yang Haoyu, Zhao Wen, Zhang Lirong, Wang Zihao, Cao Qingdao University of Science and Technology Qingdao China

ISBN: (纸本)9781665468121

According to the data selected, six evaluation indicators such as gas emission index, pollution load index, biological abundance index, land degradation index, vegetation cover index, and water network density index were used as the basis for scoring. In order to reduce the subjectivity of indicator selection and enhance the objectivity, the weight occupied by each indicator in the re-evaluation system was obtained by entropy weighting method in order to make full use of the original data. Then the TOPSIS evaluation model was established based on the index weights. Through MATLAB programming, for each year, the scoring judgment was performed. Quantitative analysis of the impact on the environment after restoration of the Seyhan Dam and the environmental conditions before and after restoration of the Seyhan Dam. Correlation analysis was performed between the index data of Seyhan Dam and the data of Beijing dust storms to find the functional relationship between each factor. And time series analysis was performed. In order to get the accuracy of the solution, for the fitted function of the correlation analysis, the variance was used to determine whether it was in a reasonable fitting interval then the entropy weighting method used in problem one was used to assign weights to the analyzed functions so as to get more objective scoring evaluation criteria. And finally, more accurate quantitative analysis data were obtained through MATLAB programming to quantitatively evaluate the role of the Sehanba Forestry in the protection against sandstorms in Beijing. © 2022 IEEE.

关键词： MATLAB

来源：评论

学校读者我要写书评

暂无评论

Challenges and New Opportunities in Diverse Approaches of Big Data Stream Analytics 3rd

Challenges and New Opportunities in Diverse Approaches of Bi...

引用

3rd international conference on Sustainable Expert Systems, ICSES 2022

作者： Bhatt, Nirav Thakkar, Amit Bhatt, Nikita Prajapati, Purvi Smt. Kundanben Dinsha Patel Department of Information Technology Chandubhai S Patel Institute of Technology Charotar University of Science and Technology Gujarat Changa India Department of Computer Science Engineering Chandubhai S Patel Institute of Technology Charotar University of Science and Technology Gujarat Changa India

ISBN: (纸本)9789811978739

The continuous generation of data develops new data analysis challenge called stream data analysis. However, most of the real-time applications require effective processing of diverse, fast, continually generating, and huge volume data. Data pre-processing plays an efficient role in producing high-quality input data. Applications in which the notion of incoming data changes over time, a single classifier could not perform better for constantly changing input, leading to the ensemble learning strategy, in which we handle stream data with multiple weak learners rather than a single strong learner. Since the properties of the streams are generally unknown, selecting an appropriate method or model is a crucial task. Meta Learning approach helps in performing stream analytics by separating the base level characteristics of input data and convert it into meta-information so that the dynamic model can be selected as per the available meta-information. Deep learning has proven to be the most promising approach specifically for high dimensional big data streams. This research study briefly describes about the different approaches involved in big data stream analytics. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Machine Condition Monitoring by Online Updated Optimized Weights Spectrum: An Industrial Motor Case Study 3

Machine Condition Monitoring by Online Updated Optimized Wei...

引用

3rd international conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2022

作者： Hou, Bingchang Kong, Jin-Zhen Chen, Yikai Liu, Jie Wang, Dong Department of Industrial Engineering and Management School of Mechanical Engineering Shanghai Jiao Tong University Shanghai Shanghai China

ISBN: (纸本)9781665492812

Machine condition monitoring (MCM) is beneficial to gaining more profits and avoiding unexpected incidents, which has received much attention from the academic and industrial fields. Fault feature extraction is crucial for MCM. Recently, an optimized weights spectrum (OWS) is proposed to extract fault features in the Fourier spectrum, however, the calculation of the OWS is restricted by the usage of fault signals. This paper proposed an online updated OWS to relieve the usage of fault signals, and a 3D OWS can be obtained to exhibit the run-to-failure fault features in the Fourier spectrum. What's more, instead of man-made experimental run-to-failure datasets, a motor dataset collected from an industrial coal mining factory validated the performance of the online updated OWS for MCM. © 2022 IEEE.

关键词： Fault diagnosis industrial case optimized weights spectrum signal processing vibration analysis

来源：评论

学校读者我要写书评

暂无评论

PCHC: A Novel Noise Label Filtering Method for Imbalanced Classification 3rd

PCHC: A Novel Noise Label Filtering Method for Imbalanced Cl...

引用

3rd international conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Hu, Libin Zhang, Yunfeng Xu, Wei Liu, Peide School of Management Science and Engineering Shandong University of Finance and Economics 7366 Erhuan East Road Lixia District Jinan China School of Computer Science and Technology Shandong University of Finance and Economics 7366 Erhuan East Road Lixia District Jinan China Shandong Lucion Investment Holdings Group Building A Jinding Center No. 2788 Aoti Xi Road Jinan China

ISBN: (纸本)9789819624676

Supervised learning datasets often suffer from the problem of noise labeling, noise label filtering (NLF) has become an appealing topic. However, the phenomenon of class imbalance is easily neglected by recent NLF methods, which results in the dataset generated by these methods still limiting the model's generalization ability. A novel noise label filtering method called Prior Confidence Heterogeneous Consensus (PCHC) was proposed in this paper for class-imbalanced datasets. PCHC can improve the performance of the classifier by avoiding the aggravation of class imbalance caused by NLF. Firstly, prior confidence (PC) strategy is proposed to preliminarily divide the original dataset into clean dataset and noisy dataset. This strategy protects minority-class samples by designing new label confidence metrics and increasing the confidence threshold for minority class samples to be recognized as noise samples;Secondly, heterogeneous consensus (HC) strategy is proposed to mine potential minority-class pseudo samples in noisy datasets. Two heterogeneous classifiers are trained on clean dataset in this strategy and the fusion decision-making ability of sample characteristics and sample space features used for mining minority-class pseudo samples in noisy dataset. Experiments on four publicly available imbalanced financial datasets have shown that the dataset generated by the PCHC method is more conducive to improving the model's generalization performance than the dataset obtained by the baseline method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Wiener filtering

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77页 << < 46 47 48 49 50 51 52 53 54 55 > >>

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：