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

107,183 篇 会议
681 篇 期刊文献
559 册 图书
2 篇 学位论文

馆藏范围

108,424 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

60,912 篇 工学
- 49,900 篇 计算机科学与技术...
- 39,812 篇 软件工程
- 13,426 篇 信息与通信工程
- 11,482 篇 生物工程
- 8,512 篇 控制科学与工程
- 6,743 篇 电气工程
- 6,349 篇 生物医学工程（可授...
- 3,866 篇 光学工程
- 3,332 篇 机械工程
- 2,984 篇 电子科学与技术（可...
- 2,763 篇 网络空间安全
- 2,719 篇 安全科学与工程
- 2,516 篇 动力工程及工程热...
- 2,319 篇 化学工程与技术
- 2,188 篇 仪器科学与技术
25,996 篇 理学
- 12,113 篇 生物学
- 12,065 篇 数学
- 5,172 篇 物理学
- 4,919 篇 统计学（可授理学、...
- 3,515 篇 系统科学
- 2,330 篇 化学
17,450 篇 管理学
- 11,016 篇 管理科学与工程(可...
- 7,614 篇 图书情报与档案管...
- 5,174 篇 工商管理
13,620 篇 教育学
- 13,419 篇 教育学
6,408 篇 医学
- 5,469 篇 临床医学
- 5,220 篇 基础医学(可授医学...
- 3,406 篇 药学(可授医学、理...
- 2,887 篇 公共卫生与预防医...
3,377 篇 法学
- 2,923 篇 社会学
1,965 篇 文学
1,766 篇 农学
1,661 篇 经济学
267 篇 艺术学
106 篇 军事学
11 篇 历史学
10 篇 哲学

主题

7,211 篇 machine learning
7,071 篇 deep learning
5,537 篇 accuracy
5,104 篇 training
4,929 篇 computational mo...
4,221 篇 education
3,834 篇 students
3,628 篇 feature extracti...
3,068 篇 support vector m...
3,068 篇 predictive model...
3,064 篇 machine learning...
3,031 篇 convolutional ne...
2,593 篇 real-time system...
2,386 篇 data models
2,238 篇 neural networks
2,032 篇 cloud computing
1,829 篇 teaching
1,491 篇 reinforcement le...
1,480 篇 artificial intel...
1,411 篇 internet of thin...

机构

814 篇 chitkara univers...
134 篇 lovely professio...
109 篇 computer science...
97 篇 karnataka bangal...
94 篇 college of compu...
89 篇 school of comput...
76 篇 school of comput...
73 篇 department of co...
72 篇 chitkara univers...
72 篇 department of co...
67 篇 department of co...
63 篇 department of co...
58 篇 school of comput...
58 篇 department of co...
52 篇 department of in...
49 篇 chitkara univers...
45 篇 chennai
43 篇 department of me...
42 篇 school of automa...
42 篇 vellore institut...

作者

71 篇 anjali t.
70 篇 shiva mehta
52 篇 li yang
42 篇 sharma vikrant
40 篇 wang lei
39 篇 rakesh kumar
35 篇 sharma neha
33 篇 wang jing
32 篇 kukreja vinay
32 篇 vinay kukreja
31 篇 lei wang
30 篇 huang yueh-min
30 篇 zhang lei
28 篇 liu bo
28 篇 yu wang
28 篇 gill kanwarparta...
27 篇 li xin
26 篇 amandeep nagpal
25 篇 vinay gautam
24 篇 zhang tao

语言

91,082 篇 英文
16,988 篇 其他
949 篇 中文
23 篇 西班牙文
12 篇 葡萄牙文
5 篇 阿拉伯文
3 篇 法文
3 篇 土耳其文
2 篇 俄文
1 篇 捷克文

检索条件"任意字段=International Conference on Learning and Teaching in Computing and Engineering"

共 108425 条记录，以下是4131-4140 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：

Virtual-scanning network for high-resolution light-field microscopy 3

Virtual-scanning network for high-resolution light-field mic...

引用

3rd international computing Imaging conference, CITA 2023

作者： Lu, Zhi Wu, Jiamin Dai, Qionghai Department of Automation Tsinghua University Beijing100084 China

ISBN: (纸本)9781510671409

Investigating sophisticated cellular and intercellular behaviors in animals is crucial to biological research, which calls for an intravital high-precision recording at ultrahigh spatiotemporal resolution. Light-field microscopy (LFM) achieves snapshot 3D imaging with a microlens array to uncouple the angular information, but at the cost of low spatial resolution. Recently, deep learning has revolved various microscopes including LFM with enhanced capabilities. However, deep learning-based LFM has limited performance in resolution, robustness and generalization ability. To address such challenges and expand the application boundaries of LFM-based technologies, we propose a learning-based framework, termed virtual-scanning network (Vs-Net) for light-field microscopy to achieve snapshot subcellular observations in vivo. © 2023 SPIE.

关键词： E-learning

来源：评论

学校读者我要写书评

暂无评论

Parameter Inversion and Deformation Prediction of Cavern Groups via Machine learning 24

Parameter Inversion and Deformation Prediction of Cavern Gro...

引用

2024 international Academic conference on Edge computing, Parallel and Distributed computing, ECPDC 2024

作者： Chen, Zhanghua Wang, Wenjun Zhu, Qizhi Zhou, Shuguang Su, Chao Chongqing Panlong Pumped Storage Power Plant Co. Ltd. Chongqing400000 China College of Water Conservancy and Hydropower Engineering Hohai University Nanjing210024 China

ISBN: (纸本)9798400718168

This study, based on an example of an underground pumped storage power station, analyzed and processed displacement monitoring data around the main plant room using the existing displacement monitoring data from the excavation of the three-layer caverns. With the assistance of the ABAQUS finite element software, a three-dimensional dynamic full-cycle construction simulation model was established. An extended elastic-viscoplastic constitutive model was chosen, and a machine learning approach was employed to inversely estimate the relevant parameters of the surrounding rock in the plant area. The inverse results were then compared with the actual measurement data, showing good agreement in terms of trends and numerical values, with errors within 10%. This approach can serve as a reference for similar efforts in the field of cavern rock inversion. © 2024 ACM.

关键词： Caves

来源：评论

学校读者我要写书评

暂无评论

EST: Integrating Explainable AI and Semi-Supervised Ensemble learning for Social Media Stress Detection

EST: Integrating Explainable AI and Semi-Supervised Ensemble...

引用

2024 IEEE international conference on computing, Applications and Systems, COMPAS 2024

作者： Tasnia, Naima Hosen, Md.Hamid Uddin, Altaf Foysal, Md. Fahim Symon, Nurul Asgar, Safa Chowdhury, Linkon East Delta University Computer Science and Engineering Chittagong Bangladesh International Islamic University Chittagong Computer Science and Engineering Chittagong Bangladesh

ISBN: (纸本)9798331529765

Social media platforms have become potential sites for analyzing people's mental health trends since they provide real-time data on users' thoughts and feelings. Automated stress detection using machine learning techniques can assist in identifying at-risk individuals, facilitating early intervention, and contributing to broader public health monitoring. This paper introduces an Ensemble Self-Training (EST) model for stress detection, combining multiple machine learning algorithms and a self-training mechanism, and provides a comprehensive interpretation of results by explainable artificial intelligence (XAI) techniques. The study utilized four distinct datasets comprising posts from popular social media sites like Reddit and Twitter. Different NLP tools, including Bigrams and Word2Vec word embeddings, created meaningful data for enhanced detection. Four machine learning classifiers- Logistic Regression, Support Vector Machine, Random Forest, and Naïve Bayes were evaluated and compared with the EST model. The EST model outperformed other models, achieving an impressive accuracy of 91.67% on the Dreaddit dataset and nearly 89% accuracy on the different datasets. Locally Interpretable Model Agnostic Explanations (LIME) enhanced the model's trustworthiness to ensure transparency and clarity of the model's predictions. © 2024 IEEE.

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Detecting Security Requirements in GitHub Issues - Novel Dataset and SmallBERT-based model 14

Detecting Security Requirements in GitHub Issues - Novel Dat...

引用

14th IEEE international conference on Cloud computing Technology and Science (CloudCom)

作者： Minina, Polina Sadovykh, Andrey Ivanov, Vladimir SOFTEAM Paris France

ISBN: (纸本)9798350339826

Cloud application security initiates with the analysis of security requirements in DevOps. This involves gathering, managing, and tracking requirements within integrated issue-tracking systems found in repositories like GitHub. DevOps offers advantages in cloud app development, such as accelerated deployment, improved collaboration, and enhanced reliability. In DevOps, while many security verification tools are automated, security requirements analysis often relies on manual procedures. User feedback plays a pivotal role in shaping cloud application requirements, and the industry actively seeks automation solutions to expedite development. Prior research has demonstrated the limited performance of conventional NLP models trained on established datasets, such as PROMISE, when employed in the context of GitHub Issues. Recent studies have explored the integration of deep learning, particularly leveraging modern large language models and transfer learning architectures, to address requirements engineering challenges. However, a significant issue persists - the transferability of these models. While these models excel when applied to datasets similar to those they were trained on, their performance often drastically falls when dealing with external domains. In our paper, we introduce an automated method for classifying requirements within issue trackers. This method utilizes a novel dataset comprising 12,000 security and non-security issues collected from open GitHub repositories. We employed a SmallBERT-based model for training and conducted a series of experiments. Our research reaffirms the challenge related to the transferability of NLP models. Simultaneously, our model yields highly promising results when applied to GitHub Issues, even in challenging scenarios involving issues from projects that were not part of the training dataset and structured requirements texts from the PROMISE dataset. In summary, our approach significantly contributes to enhancing DevOps prac

关键词： Security requirements GitHub Issues NLP Classification Dataset Machine learning Deep learning BERT

来源：评论

学校读者我要写书评

暂无评论

Deep learning Assisted Readout of In Situ Frequency Tunable Superconducting Qubits 4

Deep Learning Assisted Readout of In Situ Frequency Tunable ...

引用

4th international conference on Electronic Information engineering and Computer Communication, EIECC 2024

作者： Wang, Wei University of Macau Institute of Applied Physics and Materials Engineering 999078 China

ISBN: (数字)9798331534622

ISBN: (纸本)9798331534622

Dispersive readout of superconducting qubits is one of the most critical components of superconducting quantum computing systems. Traditional dispersive readout schemes typically employ digital signal processing technique to demodulate multiple measurements into clouds in the IQ plane, determining the qubit state through projection and threshold analysis. However, when addressing tunable qubits, this method is limited to single-frequency measurements;attempting to measure at different frequencies without adjusting the readout frequency accordingly can compromise readout fidelity. To address this, this paper proposes a deep learning-based readout scheme that can directly train and predict the readout signals corresponding to the ground and excited states of the same superconducting qubit at different frequencies under a fixed readout frequency. A supervised learning approach is utilized to construct a deep learning model based on the multilayer perceptron. The trained model can directly predict the qubit state at different frequencies within a large frequency range. Moreover, the deep learning model can not only distinguish between the ground and excited states of the qubit but also leverage its capability to handle regression problems to test any superposition state of the qubit, which has been verified through Rabi oscillation tests. Experimental results indicate that this approach can effectively discern the state within a 300 MHz tuning range of the qubit frequency, achieving a readout fidelity exceeding 92% under various magnetic flux bias and a Rabi measurement fidelity above 96%. The findings of this study underscore the efficacy of the deep learning scheme in augmenting the convenience of qubit readout processes, concurrently preserving high fidelity, which is imperative for the advancement of quantum computing technologies. © 2024 IEEE.

关键词： Qubits

来源：评论

学校读者我要写书评

暂无评论

teaching Exploration on Calculation Method Under the Background of Emerging engineering Education 5th

Teaching Exploration on Calculation Method Under the Backg...

引用

5th EAI international conference on Multimedia Technology and Enhanced learning, ICMTEL 2023

作者： Bi, Shuhui Ma, Liyao Xu, Yuan Yan, Xuehua School of Electrical Engineering University of Jinan Shandong China

ISBN: (纸本)9783031505799

The Calculation Method is a complicated theoretical and strong practical subject, which is used to study and solve the problem of numerical approximate-calculation and is used to solve mathematical problems on the computer. Under the background of emerging engineering education and under the requirement of current concept and requirements of engineering education professional certification, this paper explores the teaching ideas of Calculation Method course based on the teaching status and the existing problems. The innovative educational reform of the course is discussed from the aspects of the integration and expansion of teaching content, the combination of online and offline teaching mode driven by teaching purpose, the construction of teaching system and so on. So as to improve the knowledge of the course, increase the interaction between teachers and students, release the initiative of students, and achieve the purpose of improving the teaching effect of the course. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： teaching

来源：评论

学校读者我要写书评

暂无评论

Construction and Application of Digital College English teaching Resources on the Basis of Data Mining 3rd

Construction and Application of Digital College English Teac...

引用

3rd EAI international conference on Application of Big Data, Blockchain, and Internet of Things for Education Informatization, BigIoT-EDU 2023

作者： Yang, Xiaomin Guilin University School of Language and Literature Guangxi541002 China

ISBN: (纸本)9783031631290

The arrival of the digital era has brought many challenges and changes to traditional teaching models, teaching methods, and teaching resources in higher education. Among them, the construction and application of digital educational resources has also become an important trend in the future development of higher education. This article mainly introduces the construction and application of digital college English teaching resources based on data mining. In terms of the construction of teaching resources, this paper uses the method based on data mining technology to analyze and process a large number of student learning data and teacher teaching data within a certain period of time, mine the patterns and rules of student learning, and establish knowledge expressions, Knowledge graph and curriculum knowledge trees related to the curriculum;In terms of application, online teaching platforms are used to provide students with rich and diverse digital teaching resources, allowing them to achieve targeted learning through various social learning methods such as independent learning, autonomous dialogue, and group discussions. Practice has proven that digital college English teaching resources based on data mining can better serve the teaching practice of higher education. On the one hand, this teaching resource makes students’ learning more targeted and personalized, which is not only conducive to interaction between teachers and students, but also helps to improve students’ English learning efficiency;On the other hand, this teaching resource can provide data support and reference for teachers’ teaching practice, so as to better grasp students’ learning situation and teaching progress, and achieve optimization and improvement of the teaching process. In summary, the digital college English teaching resources proposed in this article based on data mining are a feasible and effective teaching model teaching. Based on this model, we can continuously optimize teaching content,

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Comparison of Deep learning Methods for Detecting Brain Tumor 14

Comparison of Deep Learning Methods for Detecting Brain Tumo...

引用

14th international conference on Cloud computing, Data Science and engineering, Confluence 2024

作者： Bedi, Kiran Preet Jadon, Jitendra Singh Amity School of Engineering and Technology Amity University Department of Artificial Intelligence Noida India

ISBN: (纸本)9798350344837

The intricate nature of brain tumors and their resemblance to normal brain tissues present significant challenges in effectively distinguishing and categorizing them through traditional medical image processing methods. Brain tumors pose a considerable global health risk, often leading to inaccurate diagnoses and prognoses, even with human assistance. Recent advancements in deep learning have significantly enhanced the accuracy of brain tumor detection and classification using magnetic resonance imaging (MRI) of the brain. In this research, we provide an illustrative approach for the classification of brain tumors, employing transfer learning and convolutional neural networks (CNNs). We explore several CNN architectures, including MobileNet-V2, ResNet, and Xception. Notably, MobileNet-V2 emerged as the most effective model, achieving an impressive Fl score of 98.45%. The accuracy of brain tumor categorization is pivotal for the effective evaluation of tumors and the formulation of appropriate treatment strategies. MRI is a preferred imaging modality due to its superior image quality and safety, as it does not involve ionizing radiation, unlike other imaging techniques. The integration of computational intelligence, particularly deep learning (DL), has revolutionized the diagnosis and categorization of complex clinical conditions like brain tumors. Deep learning has consistently demonstrated outstanding performance in the partitioning and classification of brain tumors. In this paper, we introduce an AI-driven method for the classification of brain tumors into benign and malignant categories using deep learning algorithms. To conduct this study, publicly available datasets comprising brain images are utilized, subject to in-depth analysis and assessment to enhance the accuracy of brain tumor classification © 2024 IEEE.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Android Malware Categorization and Characterization Using Machine learning

Android Malware Categorization and Characterization Using Ma...

引用

2024 international conference on Advances in computing, Communication, Electrical, and Smart Systems, iCACCESS 2024

作者： Nabi, Nurun Khan, Mozammel H. A. East West University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350350289

Among all the current mobile operating systems, Android has the most market share with more than three billion active users. As android is open-source, it possesses many challenges of malicious cyberattacks. Most of the android applications are now online or somehow connected to internet and for this availability of connectivity with internet, hackers can push malware into the system easily without any concern of the user, although the application was safe and secure while installing for the first time. As a result, it is becoming difficult to identify their behavior and categorize to implement protection inside android operating system. In this research, we proposed a system to categorize and characterize various types of malware based on their network traffic pattern using K-means and Decision Tree algorithm, and also proposed a diagram demonstrating how android developers can implement this system in android OS. © 2024 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

A Machine learning Approach for Reliable Object Tracking 1

引用

UNIfied conference of international Workshop on Defence Applications of Multi-Agent Systems, DAMAS 2023, international conference on Maintenance engineering, IncoME-V 2023, international conference on the Efficiency and Performance engineering Network, TEPEN 2023

作者： Amjad, Bisma Ahmed, Qasim Z. Lazaridis, Pavlos Khan, Faheem Hafeez, Maryam Zaharis, Zaharias D. School of Computing and Engineering University of Huddersfield HuddersfieldHD1 3DH United Kingdom School of Electrical and Computing Engineering Aristotle University of Thessaloniki Thessaloniki541 24 Greece

ISBN: (数字)9783031494130

ISBN: (纸本)9783031494123

Object tracking is a critical task that finds its applications in various fields including surveillance and autonomous robots. However, most of the work on object tracking has been developed on images and video data. In contrast, the aim of our work is to develop reliable object tracking system based on sequence of measurements which can be obtained from radio sensors, that are more suitable for privacy-concerned applications. In addition, we propose to use linear regression, in contrast to complex data-driven models, to demonstrate its performance against conventional tracking algorithm i.e., particle filter. Our experimental results show that LR can predict a moving object’s position with minimal error and significantly outperforms the particle filter by more than 90%. All the experiments have been validated via simulations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Machine 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500页 << < 410 411 412 413 414 415 416 417 418 419 > >>

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：