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

41,147 篇 会议
6,893 篇 期刊文献
316 册 图书

馆藏范围

48,356 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

29,956 篇 工学
- 17,997 篇 计算机科学与技术...
- 14,920 篇 软件工程
- 8,171 篇 信息与通信工程
- 5,794 篇 电子科学与技术（可...
- 5,552 篇 电气工程
- 5,070 篇 控制科学与工程
- 2,623 篇 生物工程
- 2,335 篇 光学工程
- 2,231 篇 生物医学工程（可授...
- 2,041 篇 机械工程
- 2,027 篇 动力工程及工程热...
- 1,931 篇 仪器科学与技术
- 1,504 篇 化学工程与技术
- 1,166 篇 材料科学与工程（可...
- 916 篇 安全科学与工程
- 885 篇 交通运输工程
- 784 篇 建筑学
15,741 篇 理学
- 8,320 篇 数学
- 5,237 篇 物理学
- 2,855 篇 生物学
- 2,685 篇 统计学（可授理学、...
- 1,928 篇 系统科学
- 1,572 篇 化学
6,136 篇 管理学
- 3,761 篇 管理科学与工程(可...
- 2,605 篇 图书情报与档案管...
- 2,117 篇 工商管理
1,712 篇 医学
- 1,495 篇 临床医学
- 1,390 篇 基础医学(可授医学...
- 927 篇 药学(可授医学、理...
1,096 篇 法学
- 899 篇 社会学
773 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

1,032 篇 computational mo...
993 篇 accuracy
791 篇 feature extracti...
741 篇 training
726 篇 computer science
529 篇 deep learning
502 篇 optimization
485 篇 machine learning
461 篇 predictive model...
453 篇 real-time system...
422 篇 support vector m...
408 篇 internet of thin...
397 篇 computer archite...
364 篇 neural networks
363 篇 data models
359 篇 bandwidth
340 篇 reliability
330 篇 mathematical mod...
316 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.
74 篇 díaz a.f.
66 篇 huang f.
65 篇 boumaaza j.
55 篇 coleiro a.
52 篇 kulikovskiy v.
50 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

46,003 篇 英文
1,550 篇 其他
570 篇 中文
207 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 48356 条记录，以下是4791-4800 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：

Causal Structure Learning from Imperfect Longitudinal Data in Healthcare 11

Causal Structure Learning from Imperfect Longitudinal Data i...

引用

11th IEEE International Conference on Healthcare Informatics, ICHI 2023

作者： Yang, Haoyu Tourani, Roshan Li, Jia Caraballo, Pedro Steinbach, Michael Kumar, Vipin Simon, Gyorgy University of Minnesota Dept. of Computer Science and Engineering Minneapolis United States University of Minnesota Institute for Health Informatics Minneapolis United States Mayo Clinic Dept. of Internal Medicine Rochester United States

ISBN: (纸本)9798350302639

Causal Structure Discovery (CSD) is the task of learning the set of underlying causal relationships from observational data. Due to their computational scalability and flexibility, a recently developed class of CSD methods, NOTEARS, based on a formulation allowing for continuous optimization, is gaining popularity. However, this formulation can lead to incorrect edge orientations when little/no likelihood advantage is conferred upon any edge orientation, e.g., a → b → c versus c → b → a. In longitudinal data, like electronic health records (EHRs), temporal relationships are observable among many pairs of variables. Such temporal relationship is imperfect but still suggest an orientation since causal effects cannot travel backwards in time. Following this idea, we propose methods to incorporate precedence constraints into continuous optimization-based CSD methods. Experiments on both a synthetic and two real-world datasets validate the effectiveness of the proposed precedence constraints. © 2023 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

High-Q Monolithically-Integrated Bandpass Filters Using Quarter-Spherical Resonators

High-Q Monolithically-Integrated Bandpass Filters Using Quar...

引用

2023 IEEE/MTT-S International Microwave Symposium, IMS 2023

作者： Psychogiou, Dimitra Zhao, Kunchen Tyndall National Institute Ireland University College Cork School of Engineering Ireland University of Colorado Dept. of Electrical Computer and Energy Eng. BoulderCO United States

ISBN: (纸本)9798350347647

A new class of monolithically-integrated and high-quality factor (Q) 3D bandpass filters (BPF) is reported. The proposed filter concept is based on compact high-Q quarter-spherical resonators that are significantly smaller than conventional spherical resonators. A mono-block connectorized integration concept is demonstrated using stereolithography apparatus (SLA) 3D printing. The operating principles of the quarter-spherical BPF concept are demonstrated through detailed eigen mode and full-wave electromagnetic simulations. For proof-of-concept demonstration purposes a second-order BPF prototype was manufactured and tested. It exhibited the following transfer function characteristics. Center frequency: 12.28 GHz, minimum in-band insertion loss 0.3 dB, effective quality factor (Qeff) of 1800 and fractional bandwidth of 2.8% © 2023 IEEE.

关键词： Bandpass filters

来源：评论

学校读者我要写书评

暂无评论

Comparing Algorithms for Loading Classical Datasets into Quantum Memory

Comparing Algorithms for Loading Classical Datasets into Qua...

引用

Quantum Computing and engineering (QCE), IEEE International Conference on

作者： Andriy Miranskyy Mushahid Khan Udson Mendes Dept. of Computer Science Toronto Metropolitan University Toronto Canada Dept. of Electrical and Computer Engineering University of British Columbia Vancouver Canada Quantum Technologies Team CMC Microsystems Sherbrooke Canada

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Quantum computers are gaining importance in various applications like quantum machine learning and quantum signal processing. These applications face significant challenges in loading classical datasets into quantum memory. With numerous algorithms available and multiple quality attributes to consider, comparing data loading methods is complex. Our objective is to compare (in a structured manner) various algorithms for loading classical datasets into quantum memory (by converting statevectors to circuits). We evaluate state preparation algorithms based on five key attributes: circuit dept., qubit count, classical runtime, statevector representation (dense or sparse), and circuit alterability. We use the Pareto set as a multi-objective optimization tool to identify algorithms with the best combination of properties. To improve comprehension and speed up comparisons, we also visually compare three metrics (namely, circuit dept., qubit count, and classical runtime). We compare seven algorithms for dense statevector conversion and six for sparse statevector conversion. Our analysis reduces the initial set of algorithms to two dense and two sparse groups, highlighting inherent trade-offs. This comparison methodology offers a structured approach for selecting algorithms based on specific needs. Researchers and practitioners can use it to help select data-loading algorithms for various quantum computing tasks.

关键词： Measurement Machine learning algorithms Runtime Loading Qubit Signal processing algorithms Machine learning Signal processing Optimization Faces

来源：评论

学校读者我要写书评

暂无评论

A Study on the Evaluation of Cyber Security Vulnerabilities in Medical Software

A Study on the Evaluation of Cyber Security Vulnerabilities ...

引用

International Conference on Electronics, Information and Communications (ICEIC)

作者： Jeong-Hyun Woo Jee-Hyun Koo Byung-Suk Seo Sun-Young Son Kwang-Man Ko Dept. of Computer Engineering Sang-Ji University Republic of Korea Dept. of Bigdata Science Sang-Ji University Republic of Korea Dept. of Electrical and Electronic Engineering Sang-Ji University Republic of Korea

ISBN: (数字)9798331510756

ISBN: (纸本)9798331510763

In this paper, we examine the cybersecurity vulnerability assessment method of medical software. Medical software processes patient sensitive data and is linked to various medical devices and systems in real time. Due to these characteristics, medical software is highly likely to be exposed to various cybersecurity threats such as ransomware, data leakage, and medical device hacking. Based on the international standard IEC TS 60601-4-5, we propose threat modeling, vulnerability scanning, and penetration testing as a methodology for assessing the security vulnerabilities of medical software. Through this, we can identify security vulnerabilities in advance and prepare measures to respond quickly. We can prevent security threats and improve the safety of medical software through response strategies such as security patches and updates, network separation, data encryption, and security education. In conclusion, strengthening the security of medical software is essential to maintain patient safety and the reliability of the medical system, and systematic security assessment and continuous response are required.

关键词： Threat modeling Medical devices Education Software Software reliability Encryption computer crime IEC Standards Standards Penetration testing

来源：评论

学校读者我要写书评

暂无评论

Efficiency of Wireless Communication in Cybersecurity for Data Security 10

Efficiency of Wireless Communication in Cybersecurity for Da...

引用

10th IEEE Uttar Pradesh Section International Conference on electrical, Electronics and computer engineering, UPCON 2023

作者： Shashank, R. Krishna, Konda Hari Takore, Tamirat Tagesse Singla, Atul Veena, Ch Tiwari, Mohit School of Engineering Sr Universtity Department of ECE Telangana Warangal India School of Computing Mohan Babu University Dept. of Cse Tirupati India Wachemo University Department of Electrical and Computer Engineering Ethiopia Ethiopia Lovely Professional University Phagwara India Institute of Aeronautical Engineering Hyderabad India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi India

ISBN: (纸本)9798350382471

This Article's aim is to analyse the wireless communication in Cybersecurity. The topic of this paper provides readers with a better grasp of the safety guidelines and measures that are currently on the market, as well as a quick review of the advantages and disadvantages of each kind of security approach. The potential of the system to manage, protect, and distribute confidential data is determined by protection in the world of computers. © 2023 IEEE.

关键词： Cybersecurity data security wireless communication

来源：评论

学校读者我要写书评

暂无评论

Solar Irradiance Prediction with Ensemble Learning Method as Input for Battery Operation Optimization

Solar Irradiance Prediction with Ensemble Learning Method as...

引用

IEEE Texas Power and Energy Conference (TPEC)

作者： Ray Colucci Imad Mahgoub Dept. of Computer Science & Electrical Engineering F.A.U. Boca Raton FL USA

The current use of fossil fuels as a major source of energy on a global scale has had a negative impact on the environment in terms of pollution and global warming. There is currently a paradigm shift to the utilization of renewable energy sources such as solar and wind power. However, the challenge is that these options are inherently intermittent and expensive to install. Data from these sources can be used as input to algorithms to optimize the operation of microgrids to provide energy to both residential and commercial buildings. A key component to enhance the performance of a microgrid is a battery energy storage system (BESS). Our goal is to design an algorithm to optimize battery operation. The objective of this paper is to predict the solar irradiance to provide input to battery operation optimization. We investigate the comparative performances of different strategies. The accuracy of five popular machine learning algorithms are estimated, namely Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Regression (SVR), Kernel ridge regression (KRR), and Linear Regression. Voting, stacking, and bagging ensemble methods are utilized to further enhance the accuracy. Our results show stacking to outperform the other methods. Our experiment produced better predictions than other work using the same dataset.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Sentimental Analysis of Various TV Serials in Society

Sentimental Analysis of Various TV Serials in Society

引用

International Conference on Computational Intelligence and Communication Networks (CICN)

作者： Ripa Sarkar Ratna R. Sarkar Dept. of Computer Science and Engineering BRAC University Dhaka Bangladesh Dept. of Computer Science and Engineering Jahangirnagar University Savar Bangladesh

Sentiment analysis which involves identifying emotions in the text is a widely studied topic of natural language processing. Many researchers focus on social media content like posts, tweets and reviews for their studies. In this paper, a large number of data from comments about serials on social media and internet forums in Banglish is collected and analyzed. We use NLP techniques to do the sentiment analysis of the comments. This study explores how different kinds of serials have impacted society and concentrates on how they have influenced the creation of Banglish comments. This study aims to conduct a sentiment analysis of Banglish comments generated in response to different genres of serials and to analyze their potential societal implications. Along with Long Short-Term Memory (LSTM), we use several machine-learning algorithms such as Logistic Regression (LR), Multinomial Naive Bayes (MNB), Gaussian Naive Bayes, Decision Tree (DT), AdaBoost, Random Forest (RF) and Support Vector Machine (SVM) to create this model. The SVM gives the highest accuracy among all of the machine learning algorithms.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Detection of Brain Tumor Using a Deep Learning Approach

Detection of Brain Tumor Using a Deep Learning Approach

引用

2025 International Conference on Artificial Intelligence and Data engineering, AIDE 2025

作者： Arun Kumar, S. Anand Kumar, M. Vincent, Robin Rohit Anusha M, S. Hegde, Uttam Upendra Pasha, N Nauman Dept. of Computer Studies Pune India Networks & IoT Lab Presidency University Dept. of Information Science and Engineering Bangaluru India Presidency University Bio-Intelligence Lab Dept. of Computer Science and Engineering Bangaluru India

ISBN: (纸本)9798331527518

This study introduces a deep learning-based method for classifying brain tumors using a pre-trained VGG19 convolutional neural network (CNN). By leveraging transfer learning, we adapted the VGG19 model with custom fully connected layers and trained it on MRI images to differentiate between tumor and non-tumor cases. The model's architecture includes dropout layers to minimize overfitting and enhance generalization while maintaining the robust feature extraction capabilities of the VGG19 base. We developed a Flask web application interface to make the model accessible via web-based user input, allowing users to upload MRI images and receive immediate predictions on tumor presence. Preliminary results show that proposed model can accurately classify brain tumor images with high accuracy, highlighting the potential of deep learning in automating brain tumor diagnostics. This tool could significantly aid clinicians in making rapid and accurate diagnoses, ultimately improving patient outcomes. © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Enhanced Vision Transformer with Lion Optimizer for Accurate Classification of Monkeypox Skin Images 4

Enhanced Vision Transformer with Lion Optimizer for Accurate...

引用

4th International Conference on Technological Advancements in Computational sciences, ICTACS 2024

作者： Bhatnagar, Roheet Hassan, Esraa Saber, Abeer Shams, Mahmoud Y. Elbedwehy, Samar Manipal University Jaipur Department of Computer Science and Engineering Rajasthan India Kafrelsheikh University Faculty of Artificial Intelligence Dept. of Machine Learning Kafrelsheikh33516 Egypt Damietta University Faculty of Computers and Artificial Intelligence Information Technology Dept. Damietta34517 Egypt Kafrelsheikh University Faculty of Artificial Intelligence Dept. of Data Science Kafrelsheikh33511 Egypt

ISBN: (纸本)9798350387490

Monkeypox is a contagious viral infection caused by the monkeypox virus (Mpoxvirus). Characterized by skin lesions, fever, respiratory difficulties, swollen lymph nodes, and neurological complications, MPX can be fatal. Recent outbreaks have spread the disease across Europe, Australia, the United States, and Africa. Traditionally diagnosed through PCR testing of skin lesions, this process poses significant risks to medical personnel due to potential exposure to the highly contagious virus. However, the usage artificial intelligence (AI) is revolutionizing diagnostics, providing a safer and more efficient approach to MPX detection. In this paper, a new AI technique based on vision transformer and lion optimizer for classifying Monkeypox Skin Images. The presented model used for classifying the dataset and results reached accuracy of 99.6%. © 2024 IEEE.

关键词： Classification Deep Learning Diagnosis Monkeypox

来源：评论

学校读者我要写书评

暂无评论

Misogynistic Content Detection in Roman Urdu Tweets Based on Transformer Models

Misogynistic Content Detection in Roman Urdu Tweets Based on...

引用

IEEE International Conference on Multi Topic

作者： Waseem Ullah Khan Salman Ahmed Safdar Nawaz Khan Marwat Yousaf Khan Aftab Khan Shafi Ullah Kamran Dept. of Computer Systems Engg University of Engineering & Technology Peshawar Pakistan Dept. of Electrical Engg University of Engineering & Technology Peshawar Pakistan Dept. of Computer Science Allama Iqbal Open University Islamabad Pakistan Zong CMPak Islamabad Pakistan

ISBN: (数字)9798331507213

ISBN: (纸本)9798331507220

Facebook, Instagram and Twitter serve as influential social media platforms for individuals where they express and share their thoughts, skills, knowledge and talents with a broad audience. However, these platforms are also used to disseminate offensive content including trolling and content that targets a person’s gender, religion, or race. When women become the targets of such content, it is often manifests as misogyny. In recent years, the growing prevalence of racial and verbal abuse directed at women on social media has drawn considerable attention to the issue of online misogyny and women based offending, by making the automatic detection of such offensive content an urgent priority. Moreover, many researchers have addressed misogyny detection in high resource languages i.e., English, Italian, Arabic, Hindi, and more, tackling this issue in low resource language like Roman Urdu presents a significant challenge. In this paper, a framework is proposed for detection of misogynistic content from Roman Urdu tweets. This paper leverages well known transformer models such as BERT, RoBERTa, GPT-2, and XLNet to train and evaluate misogyny detection performance. The research findings reveal that RoBERTa surpasses the other models in misogyny detection, by achieving the highest accuracy, precision, F1-score and recall i.e., 90.87%, 90%, 89%, and 91%, respectively.

关键词： Accuracy Social networking (online) Blogs Linguistics Transformers Web sites Reliability Multimedia communication

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 << < 476 477 478 479 480 481 482 483 484 485 > >>

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：