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

755 篇 会议
8 册 图书
6 篇 期刊文献

馆藏范围

769 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

470 篇 工学
- 386 篇 计算机科学与技术...
- 289 篇 软件工程
- 172 篇 信息与通信工程
- 93 篇 电气工程
- 84 篇 生物工程
- 75 篇 控制科学与工程
- 71 篇 生物医学工程（可授...
- 46 篇 网络空间安全
- 39 篇 安全科学与工程
- 38 篇 交通运输工程
- 36 篇 电子科学与技术（可...
- 29 篇 仪器科学与技术
- 26 篇 机械工程
- 25 篇 光学工程
- 21 篇 化学工程与技术
206 篇 理学
- 100 篇 数学
- 91 篇 生物学
- 47 篇 统计学（可授理学、...
- 43 篇 物理学
- 39 篇 系统科学
- 29 篇 化学
133 篇 管理学
- 82 篇 图书情报与档案管...
- 75 篇 管理科学与工程(可...
- 27 篇 工商管理
67 篇 医学
- 57 篇 临床医学
- 46 篇 基础医学(可授医学...
- 39 篇 药学(可授医学、理...
22 篇 法学
- 21 篇 社会学
16 篇 农学
- 16 篇 作物学
15 篇 教育学
- 14 篇 教育学
9 篇 经济学
5 篇 军事学
1 篇 文学

主题

205 篇 machine learning
60 篇 signal processin...
47 篇 feature extracti...
45 篇 deep learning
45 篇 signal processin...
39 篇 support vector m...
36 篇 machine learning...
31 篇 training
27 篇 accuracy
22 篇 computational mo...
18 篇 neural networks
16 篇 data models
15 篇 predictive model...
15 篇 image processing
14 篇 natural language...
14 篇 forecasting
13 篇 electroencephalo...
13 篇 real-time system...
13 篇 classification
13 篇 artificial intel...

机构

7 篇 chitkara univers...
4 篇 school of comput...
4 篇 lloyd law colleg...
3 篇 telangana hydera...
3 篇 school of comput...
3 篇 institute of aer...
3 篇 lloyd institute ...
3 篇 school of electr...
3 篇 department of co...
3 篇 school of comput...
3 篇 department of el...
3 篇 department of me...
3 篇 central universi...
3 篇 lloyd law colleg...
3 篇 lloyd institute ...
3 篇 college of compu...
3 篇 school of electr...
3 篇 co. ltd.
2 篇 school of presch...
2 篇 beijing institut...

作者

4 篇 shaik subhani
4 篇 wathiq mansoor
4 篇 mansoor wathiq
3 篇 anand r.
3 篇 subba rao s.p.v.
3 篇 gabbouj moncef
3 篇 yazici ibrahim
3 篇 i̇brahim yazici
3 篇 k mayuri
2 篇 rui wang
2 篇 anas abou el kal...
2 篇 guo jianxin
2 篇 mehdi salkhordeh...
2 篇 a l n rao
2 篇 shuja mirza
2 篇 yatika gori
2 篇 ahmed qtaishat
2 篇 cao jiuwen
2 篇 mirza shuja
2 篇 liu yang

语言

741 篇 英文
24 篇 其他
12 篇 中文

检索条件"任意字段=6th International Conference on Signal Processing and Machine Learning, SPML 2023"

共 769 条记录，以下是321-330 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：

Application of machine learning and Blockchain Technology in Improving Supply Chain Financial Risk Management 6

Application of Machine Learning and Blockchain Technology in...

引用

6th international conference on Contemporary Computing and Informatics, IC3I 2023

作者： Atta, Anas Ahmad Bani Ahmad, Ahmad Yahiya Ahmad Bani Allahham, Mahmoud Izzat Sisodia, Dharini Raje Singh, Rupesh Roshan Maginmani, Umme Habiba Middle East University Financial Technology Faculty of Business Financial and Accounting Science Department Amman11831 Jordan Middle East University Financial and Accounting Science Department Amman11831 Jordan College of Business LTUC Jordan Army Institute of Management and Technology Management India Block-14Mittal School of Business Lovely Professional University Punjab Phagwara India Secab Institute of Engineering and Technology Department of Computer Science & Engineering Karnataka Vijayapur India

ISBN: (纸本)9798350304480

the database used by blockchain innovation is run by numerous components and creates a network pattern using hash indexes. the blockchain employs numerous nodes and transmits numerous data access points, decreasing reliance on the primary Internet server and preventing the danger of data destruction and server breakdown. the data files saved in the blockchain are protected using encryption techniques to maintain their authenticity and prevent illegally added or discarded data files. With technological characteristics like non-tampering, distributed ledger, and reliability, blockchain innovations and machine learning have innate benefits in supply chain finance. they also have great prospects to construct faith in order to overcome the major issues in supply chain finance, which is helpful for fostering economic advancement in the Tonkin Gulf region. this paper focuses on introducing the study on using blockchain innovation in supply chain finance in the Tonkin Gulf region and aims to offer suggestions on how supply chain finance could evolve there using blockchain innovation. this paper suggests supply chain finance game applications for pertinent investigations as well as blockchain innovation, supply chain banking threats assessment on the blockchain and machine learning, and supply chain finance implementation study methodologies in the Tonkin Gulf region. the empirical findings presented in this paper demonstrate that the built blockchain supply chain finance platform has an algorithm with an overall processing time of 4.10 seconds, a computational efficiency that is quicker, and the ability to more accurately analyse the pertinent concerns. © 2023 IEEE.

关键词： Blockchain technology machine learning supply chain financial risk

来源：评论

学校读者我要写书评

暂无评论

Advancing a Cascaded machine learning Approach for the Accurate Estimation of Antenna Parameters

Advancing a Cascaded Machine Learning Approach for the Accur...

引用

international conference on signal processing and Information Security (ICSPIS)

作者： Abigail Copiaco Rida Gadhafi Husameldin Mukthar Wathiq Mansoor College of Engineering and IT University of Dubai Dubai United Arab Emirates

this paper proposes the use of decision trees and linear regression to accurately predict the parameters of an antenna. Antennas remain a crucial component within RF systems. Computing pivotal antenna parameters such as the operational frequency, reflection coefficient (S11), antenna bandwidth, and radiation characteristics can prove to be a laborious endeavor. Obtaining these parameters necessitates meticulous optimizations in antenna design, consuming both time and human resources. In this study, we have undertaken an initial investigation into the utilization of machine learning regression techniques to predict antenna parameters, including the operating frequency, minimum value of S11 in dB, and bandwidth. A classical printed monopole antenna design is used in a case study. A three-step cascaded machine learning model trained on a four-dimensional initial feature set is used. Notably, Fine Gaussian support vector machines (SVM) provided the best result for S11 estimation, yielding a root mean square error (RMSE) of around 0.12, while fine decision trees provided the best results in the field of frequency optimization, resulting in an average RMSE of approximately 0.3. Finally, cubic SVMs resulted in an optimal RMSE of 0.009 for bandwidth approximation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Experimental Benchmarking of Quantum machine learning Classifiers

Experimental Benchmarking of Quantum Machine Learning Classi...

引用

international conference on signal processing and Information Security (ICSPIS)

作者： Mohamed Aly Salma Fadaaq Omnia Abu Warga Qassim Nasir Manar Abu Talib Department of Computer Science University of Sharjah Sharjah UAE Department of Computer Engineering University of Sharjah Sharjah UAE

Quantum machine learning (QML) has emerged as an interdisciplinary field that harnesses the potential of quantum computing to revolutionize classical machine learning paradigms. this paper presents a benchmarking study focused on four quantum classifier algorithms: Quantum Support Vector Classifier (QSVC), Variational Quantum Circuit (VQC), Quantum Neural Network Classifier (QNNC) and Pegasos Quantum Support Vector Classifier (PegasosQSVC). these quantum classifiers hold promise for unlocking quantum advantages in classification tasks. However, a systematic assessment of their performance across diverse datasets is yet to be fully explored. In this research study, we evaluate and compare the classification performance of quantum machine learning classifiers on various datasets (Breast Cancer, Diabetes, and Titanic) and compare them to a classical model. Our findings revealed that PegasosQSVC consistently maintained high performance across all datasets with the highest average accuracy, recall, and F1-score values of 0.81, 0.72, and 0.71, respectively, followed by VQC, followed by VQC, while QSVC and QNNC perform variably. Nevertheless, QSVC was found to balance performance and training time, achieving an average accuracy of 0.81 and a training time of 177 seconds. Overall, the classical model surpassed QML models as it was up to 10% higher in average accuracy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Intelligent signal processing Method Based on Random Forest and CNN

An Intelligent Signal Processing Method Based on Random Fore...

引用

IEEE international conference on Automation, Electronics and Electrical Engineering (AUTEEE)

作者： Chaoyuan Hao Longzhong Jin Yuheng Qian Zuofu Guo Lanzhou University Lanzhou China

In fields such as digital communication, audio processing, and image processing, the techniques for encoding and decoding signals and performing noise reduction play a pivotal role in ensuring the quality of information transmission. this paper tends to harness the capabilities of machine learning and neural networks to devise intelligent solutions for signal encoding and decoding with the objectives of enhancing signal quality, alleviating congestion, and optimizing communication systems. Firstly, the experiment focuses on using random forests and Convolutional Neural Networks (CNN) to identify signal encoding methods, followed by the implementation of efficient noise reduction techniques. this paper findings demonstrate that this integrated approach attains an accuracy level of approximately 92% in recognizing various signal encoding methods. Furthermore, it has been observed that when subjected to interference, post-processing leads to significant improvements in the Root Mean Square Error (RMSE) associated with each encoding method, thus ensuring high-quality noise reduction.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Analysis and Prediction of Heart Disease Based on machine learning Algorithms

Analysis and Prediction of Heart Disease Based on Machine Le...

引用

6th international conference on Intelligent Computing and signal processing (ICSP)

作者： Haonan Yu Department of Electronic Information Engineering Nanjing Tech University Nanjing China

As the incidence of heart disease continues to rise globally, there is an urgent need for accurate and efficient methods to detect and prevent this debilitating condition. To address this need, this paper proposes a machine learning-based medical system for predicting the likelihood of heart disease occurrence in patients. the study utilizes the UCI dataset to analyze multiple indicators using eight different algorithms to identify the most accurate and comprehensive attributes for predicting heart disease. the results reveal the algorithm with the highest accuracy and most reliable attributes, which are then integrated into a practical medical treatment system. this system is specifically designed for effective application in real-life medical settings to improve the accuracy of heart disease diagnosis and reduce the burden on hospitals. the proposed system has significant implications for enhancing the early detection and management of heart disease, thus enabling timely intervention and treatment. the integration of machine learning algorithms in medical practice has the potential to significantly improve patient outcomes, reduce healthcare costs and advise patients to receive effective care from healthcare professionals timely.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Multi-Scale Feature Aggregation Based Lightweight Network for Audio-Visual Speech Enhancement 48

A Multi-Scale Feature Aggregation Based Lightweight Network ...

引用

48th IEEE international conference on Acoustics, Speech and signal processing, ICASSP 2023

作者： Xu, Haitao Wei, Liangfa Zhang, Jie Yang, Jianming Wang, Yannan Gao, Tian Fang, Xin Dai, Lirong NERC-SLIP Hefei China Machine Learning Group Ethereal Audio Lab Shenzhen China Tsinghua Shenzhen International Graduate School Shenzhen China

ISBN: (纸本)9781728163277

Audio-visual speech enhancement (AVSE) was shown to be superior over conventional audio-only counterpart for improving the speech quality. However, most existing AVSE models are heavyweight in the sense of parameter count, which is inappropriate for the deployment and practical applications. In this paper, we therefore present a lightweight AVSE approach (called M3Net) by incorporating several multi-modality, multi-scale and multi-branch strategies. three multi-scale techniques are designed for the visual and audio streams, including multi-scale average pooling (MSAP), multi-scale ResNet (MSResNet) and multi-scale short time Fourier transform (MSSTFT). It is shown that each multi-scale module positively contributes to the performance. Also, we consider four skip connections for the audio-visual feature aggregation, which have a great complementary effect on the designed multi-scale techniques. Experimental results show that these techniques are flexible in combination with existing approaches, and more importantly obtain a comparable performance with a smaller model size compared to the heavyweight networks. © 2023 IEEE.

关键词： Speech enhancement

来源：评论

学校读者我要写书评

暂无评论

Software-Defined Wireless Communication Systems for Heterogeneous Architectures 23

Software-Defined Wireless Communication Systems for Heteroge...

引用

29th Annual international conference on Mobile Computing and Networking, MobiCom 2023

作者： Volz, David Koch, Andreas Bloessl, Bastian Technical University of Darmstadt Darmstadt60011226 Germany

ISBN: (纸本)9781450399906

Future cellular networks will be programmable and increasingly software-defined with APIs to hook into the communication stack closer and closer to the physical layer. this allows operators, for example, to plug-in third-party machine learning algorithms to optimize performance. At the same time, this flexibility implies that compute resources cannot be provisioned statically but have to be distributed dynamically during runtime. While the hardware platforms for such systems are available, we lack suitable software frameworks that help to realize such systems. In this demonstration, we present two Open Source projects that fill this gap: FutureSDR, a portable real-time signal processing framework with native support for accelerators (like GPUs and FGPAs);and IPEC, which enables fully automatic composition of multi-accelerator FPGA designs. We believe that these tools - especially in combination with each other - can provide the base for building research prototypes and allow experimentation with software-defined wireless communication systems. © 2023 Owner/Author(s).

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

A Hybrid machine learning Framework to Improve Parkinson’s Disease Prediction Accuracy

A Hybrid Machine Learning Framework to Improve Parkinson’s ...

引用

international conference on signal processing and Information Security (ICSPIS)

作者： Ronak Bediya Ravikumar R N Krishnanand Mishra Khushi Kandoi Siddhant Gautam Singh Sushil Kumar Singh Department of Computer Engineering Marwadi University Rajkot India

Parkinson's Disease (PD) is one of the second most prevalent neurodegenerative ailment worldwide, behind Alzheimer's disease, according to the World Health Organization (WHO). PD affects both men and women equally and tends to become more prevalent as people age. the prevalence of PD in those over 65 ranges from 2% to 3%. In this research we have used Parkinson’s Dataset from UCI repository and employed machine learning and Deep learning algorithms. the research study suggests a hybrid approach for predicting PD that combines Artificial Neural Networks (ANN), Recurrent Neural Networks (RNN), and Decision Trees (DT). It performs better than individual models and offers guidance for selecting a course of therapy. When we evaluated the accuracy of different models, the findings showed that the (ANN) alone could only reach 84% accuracy whereas the combination of ANN and RNN could obtain 85% accuracy. the hybrid algorithm's accuracy was further boosted to 88% with the use of Decision Trees (DT). these findings highlight the value of utilizing a variety of machine learning techniques to enhance Parkinson's disease prediction in order to uncover pertinent characteristics, capture temporal dependencies, and enhance understanding for clinical decision-making to enhance the quality of life over a growing population.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Smart Health Application for Real-Time Cardiac Disease Detection and Diagnosis Using machine learning on ECG Data 6th

A Smart Health Application for Real-Time Cardiac Disease De...

引用

6th IFIP international conference on Internet of things, IFIP IoT 2023

作者： Utsha, Ucchwas Talukder Hua Tsai, I. Morshed, Bashir I. Department of Computer Science Texas Tech University Lubbock United States

ISBN: (纸本)9783031458774

Cardiac disease, also referred to as cardiovascular disease, is a collection of conditions that affect the heart and blood vessels. Medical professionals typically use a combination of medical history, physical examination, and various diagnostic tests, such as electrocardiograms (ECG/EKG), echocardiograms, and stress tests, to diagnose cardiac diseases. In response to this issue, we are introducing a mobile application that continuously monitors electrocardiogram signals and displays both average and instantaneous heart rates. the aim of this project is to detect and diagnose cardiac diseases so that patients can become informed about their heart health and take appropriate actions based on the results obtained. To identify diseases from real-time ECG data, we used machine learning (ML) classifiers and compared them with offline data to validate the classification. the model we used in our application is pre-trained on the MIT-BIH Arrhythmia Database, which contains a wide range of heart conditions. We used Artificial Neural Network (ANN) as a pre-trained model for multiclass detection as it performed the best among ML models, showing an overall accuracy of 94%. the performance of the model is evaluated by testing it on the application using MIT-BIH test Dataset. On the application, the beat-detecting pre-trained model showed an overall accuracy of 91.178%. the results indicate that the Smart-Health application can accurately classify heart diseases, providing an effective tool for early detection and monitoring of cardiac conditions. © 2024, IFIP international Federation for Information processing.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

A Method of Advanced Persistent threat Data processing Based on Ensemble learning

A Method of Advanced Persistent Threat Data Processing Based...

引用

6th international conference on Intelligent Computing and signal processing (ICSP)

作者： Xuelong Wang Xin Zheng Yang Tu School of Computer Science Xi'an Shiyou University Xi'an Shaanxi China Internet data center Xi'an Shiyou University Xi'an Shaanxi China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Finding the features with the highest correlation degree in the source APT data from network security devices is essential for preprocessing the data in order to train models that will increase the accuracy of APT attack classification. the preprocessing, cleaning, and feature transformation of the dataset are the first steps in the application of data mining techniques in this work. Variancethreshold is ultimately chosen for feature selection to create the optimal feature subset after a range of feature selection techniques are used for experimental comparison. the best feature subset is then used to compare and evaluate several machine learning algorithms, and by integrating ensemble learning methods, the VT-stacking model is recommended. the experimental results demonstrate that the VT-stacking model developed in this paper achieves 97.3% accuracy in categorizing APT assaults after preprocessing the APT data.

关键词： Accuracy machine learning algorithms Firewalls (computing) Stacking Network security signal processing Feature extraction Data processing Data models Ensemble learning

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 << < 29 30 31 32 33 34 35 36 37 38 > >>

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：