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

615 篇 会议
190 篇 期刊文献
2 册 图书

馆藏范围

807 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

671 篇 工学
- 547 篇 计算机科学与技术...
- 487 篇 软件工程
- 189 篇 信息与通信工程
- 112 篇 控制科学与工程
- 77 篇 电子科学与技术（可...
- 73 篇 电气工程
- 46 篇 生物医学工程（可授...
- 45 篇 光学工程
- 32 篇 生物工程
- 31 篇 仪器科学与技术
- 27 篇 机械工程
- 25 篇 化学工程与技术
- 21 篇 建筑学
- 18 篇 动力工程及工程热...
- 18 篇 土木工程
- 17 篇 材料科学与工程（可...
376 篇 理学
- 283 篇 数学
- 82 篇 物理学
- 69 篇 统计学（可授理学、...
- 36 篇 生物学
- 29 篇 化学
- 19 篇 系统科学
184 篇 管理学
- 110 篇 图书情报与档案管...
- 87 篇 管理科学与工程(可...
- 55 篇 工商管理
41 篇 教育学
- 41 篇 教育学
31 篇 法学
- 24 篇 社会学
27 篇 医学
- 23 篇 临床医学
- 22 篇 基础医学(可授医学...
18 篇 经济学
- 18 篇 应用经济学
5 篇 农学
1 篇 文学
1 篇 艺术学

主题

12 篇 software enginee...
10 篇 data mining
9 篇 wireless telecom...
8 篇 world wide web
8 篇 artificial intel...
7 篇 computer science
7 篇 network protocol...
7 篇 wireless sensor ...
7 篇 students
7 篇 forecasting
7 篇 cryptography
6 篇 internet of thin...
6 篇 reliability
6 篇 learning systems
6 篇 algorithms
6 篇 mobile telecommu...
6 篇 educational inst...
6 篇 energy consumpti...
6 篇 semantics
6 篇 image processing

机构

9 篇 dept. of compute...
8 篇 dept. of compute...
5 篇 dept. of info. a...
5 篇 dept. of compute...
5 篇 department of el...
4 篇 institute of inf...
4 篇 info. processing...
4 篇 osaka university
4 篇 microsoft resear...
4 篇 dept. of compute...
4 篇 department of co...
4 篇 university of to...
4 篇 dept. of info. a...
4 篇 deepwise ai lab
4 篇 waseda universit...
4 篇 dept. of info. a...
4 篇 department of co...
4 篇 dept. of info. a...
3 篇 dept. of compute...
3 篇 dept of computer...

作者

8 篇 lee insup
7 篇 sasase i.
6 篇 jie wu
6 篇 wang yizhou
6 篇 yang cheng-ying
5 篇 chen jong-shin
5 篇 huang hsiang-che...
5 篇 jong-shin chen
5 篇 cheng-ying yang
5 篇 chen yueh-hong
5 篇 hwang min-shiang
4 篇 kayas golam
4 篇 hu xiaohua
4 篇 yao jenq-foung j...
4 篇 funabiki nobuo
4 篇 mohamed younis
4 篇 hossain mahmud
4 篇 ohtsuki t.
4 篇 pazzani michael ...
4 篇 min-shiang hwang

语言

772 篇 英文
14 篇 日文
12 篇 其他
9 篇 中文

检索条件"机构=Dept. of Info. Engineering and Computer Science"

共 807 条记录，以下是11-20 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 Bayesian Reinfo.cement Learning Method for Periodic Robotic Control Under Significant Uncertainty

A Bayesian Reinforcement Learning Method for Periodic Roboti...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Yuanyuan Jia Pedro Miguel Uriguen Eljuri Tadahiro Taniguchi Dept. of Info. Science and Engineering Ritsumeikan University Japan

This paper addresses the lack of research on periodic reinfo.cement learning for physical robot control by presenting a 3-phase periodic Bayesian reinfo.cement learning method for uncertain environments. Drawing on cognition theory, the proposed approach achieves effective convergence with fewer training episodes. The coach-based demonstration phase narrows the search space and establishes a foundation for a coarse-to-fine control strategy. The reconnaissance phase enhances adaptability by discovering a valuable global repre-sentation, and the operation phase produces accurate robotic control by applying the learned representation and periodically updating local info.mation. Comparative analysis with state-of-the-art methods validates the efficacy of our approach on exemplar control tasks in simulation and a biomedical project involving a simulated cranial window task.

关键词：

来源：评论

学校读者我要写书评

暂无评论

PAC PREDICTION SETS UNDER COVARIATE SHIFT 10

PAC PREDICTION SETS UNDER COVARIATE SHIFT

引用

10th International Conference on Learning Representations, ICLR 2022

作者： Park, Sangdon Dobriban, Edgar Lee, Insup Bastani, Osbert Dept. of Computer & Info. Science PRECISE Center University of Pennsylvania United States Dept. of Statistics & Data Science The Wharton School University of Pennsylvania United States

An important challenge facing modern machine learning is how to rigorously quantify the uncertainty of model predictions. Conveying uncertainty is especially important when there are changes to the underlying data distribution that might invalidate the predictive model. Yet, most existing uncertainty quantification algorithms break down in the presence of such shifts. We propose a novel approach that addresses this challenge by constructing probably approximately correct (PAC) prediction sets in the presence of covariate shift. Our approach focuses on the setting where there is a covariate shift from the source distribution (where we have labeled training examples) to the target distribution (for which we want to quantify uncertainty). Our algorithm assumes given importance weights that encode how the probabilities of the training examples change under the covariate shift. In practice, importance weights typically need to be estimated;thus, we extend our algorithm to the setting where we are given confidence intervals for the importance weights. We demonstrate the effectiveness of our approach on covariate shifts based on DomainNet and ImageNet. Our algorithm satisfies the PAC constraint, and gives prediction sets with the smallest average normalized size among approaches that always satisfy the PAC constraint. © 2022 ICLR 2022 - 10th International Conference on Learning Representationss. All rights reserved.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Crime-Intent Sentiment Detection on Twitter Data Using Machine Learning 8

Crime-Intent Sentiment Detection on Twitter Data Using Machi...

引用

8th International Conference on Automation, Control and Robotics engineering, CACRE 2023

作者： Bokolo, Biodoumoye George Ogegbene-Ise, Ebikela Chen, Lei Liu, Qingzhong Sam Houston State University Dept. of Computer Science HuntsvilleTX United States Kennesaw State University Dept. of Comp. and Software Eng. KennesawGA United States Georgia Southern University Dept. of Info. Tech. Statesboro Georgia

ISBN: (纸本)9798350302776

This research examines sentiment analysis in the context of crime intent using machine learning algorithms. A comparison is made between a crime intent dataset generated from a Twitter developer account and Kaggle's sentiment140 dataset for Twitter sentiment analysis. The algorithms employed include Support Vector Machine (SVM), Naïve Bayes, and Long Short-Term Memory (LSTM). The findings indicate that LSTM outperforms the other algorithms, achieving high accuracy (97%) and precision (99%) in detecting crime tweets. Thus, it is concluded that the crime tweets were accurately identified. © 2023 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Developing Introductory computer science Pedagogy for Black Boys

Developing Introductory Computer Science Pedagogy for Black ...

引用

2021 Research on Equity and Sustained Participation in engineering, Computing, and Technology, RESPECT 2021

作者： Isaac, Joseph Gardner-Mccune, Christina University of Florida Dept. of Computer and Info. Science and Engineering GainesvilleFL32611 United States

ISBN: (纸本)9781665449052

Broadening participation in computing research and initiatives have addressed the longstanding underrepresentation of various populations - including women, Black people, Latinx people, and persons with disabilities. Although there has been an increase in underrepresented populations participating in computing, there is still a need to further investigate and build on these efforts considering there is limited research on the participation of black boys. This position paper discusses the need for an increase in Black male participation in computer science and proposes a framework for developing an introductory computer science curriculum tailored for black middle school boys. This paper will support the proposed framework by identifying factors for how boys learn and the unique needs of black boys in an educational context;then merging those factors with effective strategies used for women and people of color participating in computer science. © 2021 IEEE.

关键词： Education computing

来源：评论

学校读者我要写书评

暂无评论

Real-Time Population Density Estimation in Dubai Through Deep Learning and Car Counting in Satellite Images

Real-Time Population Density Estimation in Dubai Through Dee...

引用

2023 International Conference on Machine Learning and Cybernetics, ICMLC 2023

作者： Zaki, Nazar Singh, Harsh Kiong, Loo Chu Zaki, Nadeen Alnuaimi, Salama College of Info. Tech. United Arab Emirates Uni. Dept. of Computer Science and Software Eng. Al Ain15551 United Arab Emirates Universiti Malaya Faculty of Computer Science & Information Technology Kuala Lumpur50603 Malaysia

ISBN: (纸本)9798350303780

Accurately estimating population density is a crucial component of policy-making for the development of any country. Traditionally, population density has been estimated through labor-intensive surveys that can be time-consuming and prone to error. Census data, while useful, is only collected once every 10 years or so and can take a long time to process, depending on the geography and population of the region. This makes it difficult for organizations that require up-to-date population density info.mation for instant policy designing. To address this issue, we propose a novel approach to estimate population density using satellite imagery. Our method leverages the correlation between car density and population density. Specifically, we validate this assumption by counting cars over Dubai city using a Faster RCNN object detector with a ResNeXt-101 (32× 8d)-FP backbone and calculating the correlation between car density and population density. Our results show a significant value of the Pearson correlation coefficient, demonstrating a strong relationship between population density and car density. This innovative approach allows for the rapid estimation of population density, without the need for time-consuming and labor-intensive surveys. © 2023 IEEE.

关键词： Satellite imagery

来源：评论

学校读者我要写书评

暂无评论

Angelic Patches for Improving Third-Party Object Detector Performance

Angelic Patches for Improving Third-Party Object Detector Pe...

引用

Conference on computer Vision and Pattern Recognition (CVPR)

作者： Wenwen Si Shuo Li Sangdon Park Insup Lee Osbert Bastani Dept. of Computer & Info. Science University of Pennsylvania School of Cybersecurity & Privacy Georgia Institute of Technology

Deep learning models have shown extreme vulnerability to distribution shifts such as synthetic perturbations and spatial transformations. In this work, we explore whether we can adopt the characteristics of adversarial attack methods to help improve robustness of object detection to distribution shifts such as synthetic perturbations and spatial transformations. We study a class of realistic object detection settings wherein the target objects have control over their appearance. To this end, we propose a reversed Fast Gradient Sign Method (FGSM) to obtain these angelic patches that significantly increase the detection probability, even without pre-knowledge of the perturbations. In detail, we apply the patch to each object instance simultaneously, strengthening not only classification, but also bounding box accuracy. Experiments demonstrate the efficacy of the partial-covering patch in solving the complex bounding box problem. More importantly, the performance is also transferable to different detection models even under severe affine transformations and deformable shapes. To the best of our knowledge, we are the first object detection patch that achieves both cross-model efficacy and multiple patches. We observed average accuracy improvements of 30% in the real-world experiments. Our code is available at: https://***/averysi224/angelic_patches.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhancing the Transportation of Students with Disabilities on Campus 3

Enhancing the Transportation of Students with Disabilities o...

引用

3rd International Conference on Innovative Research in Applied science, engineering and Technology, IRASET 2023

作者： Ibrahim, Walid Alshamsi, Shaikha Alnuaimi, Salama Alneyadi, Alia Aldhaheri, Salama Alsalmi, Aysha Amer, Hoda Uae University Network and Comp. Eng. Dept. Al ain United Arab Emirates United Arab Emirates Univeristy Info. Systems & Security Dept. Al Ain United Arab Emirates United Arab Emirates Univeristy Computer Science Dept. Al Ain United Arab Emirates

ISBN: (纸本)9798350398366

Access to education has always been aconstitutional right provided by countries to their citizens. To fosterinclusion and equality, many countries have made tangible efforts recently toinclude students with disabilities in mainstream education. A recentministerial resolution by the UAE government directs education institutions tocater to the needs of students with disabilities. Moving comfortably, andefficiently on campus is a basic need for students to attend lectures, labsessions, and social activities in different buildings. However, this basicneed forms another major challenge for students with disabilities. Thischallenge is usually aggravated in gated campuses where private cars are notallowed. In such situations, students with disabilities rely on the specialtransportation service provided by the education institution to move on ***, this service is ad-hoc in nature and requires students to communicatewith the service center to book the service in advance. The service booking isdone manually, which reduces the utilization of the available vehicles, andincreases the students' waiting time and the possibility that the booking isrejected. This paper introduces a mobile application with an intelligentbooking system to automate the booking requests. The aim of the system isreducing the students' wait time and booking rejection rate while maximizingthe utilization of the available vehicles. © 2023 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Securing Against Deception: Exploring Phishing Emails Through ChatGPT and Sentiment Analysis 22

Securing Against Deception: Exploring Phishing Emails Throug...

引用

22nd IEEE/ACIS International Conference on Software engineering Research, Management and Applications, SERA 2024

作者： Sayyafzadeh, Shahrzad Weatherspoon, Mark Yan, Jie Chi, Hongmei Florida A and M University Dept. of Comp. & Info Sciences TallahasseeFL32307-5100 United States FAMU-FSU College of Engineering TallahasseeFL32301 United States Bowie State University Dept. of Computer Science BowieMD United States

ISBN: (纸本)9798350391343

The origin of large language models (LLMs) has left an indelible mark on various domains, most notably in natural language processing and artificial intelligence. While extensive research has delved into LLMs like ChatGPT 4 for tasks such as code generation and text synthesis, their application in identifying malicious web content, particularly phishing web sites, still needs to be explored. To confront the growing wave of automated cyber threats facilitated by LLMs, automating the detection of malicious email content. This paper investigates the utilization of Natural Language Processing (NLP) techniques, including VADER (valence aware dictionary and sentiment Reasoner) sentiment analysis and Large Language Models (LLMs) to strengthen the detection of phishing emails, offering enhanced defense mechanisms against cyber threats by analyzing the diverse attributes of phishing emails, including sender details, URLs, textual content, and linguistic characteristics. In this study, we leverage the power of ChatGPT's 4 state-of-the-art language models and employ Natural Language Processing (NLP) techniques. We develop an intelligent system that identifies and flags potential phishing attempts in spam emails and URLs. Our experiments using GPT-4 on our dataset demonstrated promising results, achieving an accuracy of 92%. These findings underscore LLMs' potential, including VADER sentiment analysis, to detect rapidly and accurately phishing emails, safeguarding cybersecurity challenges and protecting users from online fraud and phishing attempts. © 2024 IEEE.

关键词： Phishing

来源：评论

学校读者我要写书评

暂无评论

BERT-Based Sentiment Forensics Analysis for Intrusion Detection 22

BERT-Based Sentiment Forensics Analysis for Intrusion Detect...

引用

22nd IEEE International Conference on Machine Learning and Applications, ICMLA 2023

作者： Sayyafzadeh, Shahrzad Chi, Hongmei Xu, Weifeng Roy, Kaushik Dept. of Comp. & Info. Sciences Florida A&m University TallahasseeFL32307 United States School of Criminal Justice the University of Baltimore BaltimoreMD United States Dept. of Computer Science North Carolina a&t State University GreensboroNC United States

ISBN: (纸本)9798350345346

The need for effective intrusion detection and user behavior analytics in cybersecurity has reached unprecedented levels. By leveraging the power of BERT, a pre-trained language model known for its contextual understanding, the goal is to uncover latent patterns and insights within textual data to identify potential threats and anomalous user behavior. This study aims to further advance network analysis capabilities by integrating BERT (Bidirectional Encoder Representations from Transformers) for fine-tuning an Long Short-Term Memory (LSTM) model with attention mechanisms. By incorporating attention mechanisms, these models intelligently prioritize and focus on relevant parts of the input data, allowing them to capture corpus in our linguistic resource and improve overall performance. The study explores advanced modeling techniques to gain the emotional tone in proactive intrusion detection. We achieved 92% accuracy and precision of 89% on our sentiment-based model into traffic analysis and network passive attacks. © 2023 IEEE.

关键词： BERT Digital forensics Intrusion detection LSTM Natural language processing

来源：评论

学校读者我要写书评

暂无评论

Health Clinic System with e-Health and Android Technology for University in Saudi Arabia 6

Health Clinic System with e-Health and Android Technology fo...

引用

6th International Conference on computer and info.mation sciences, ICCOINS 2021

作者： Aljohani, Fatimah Ayed Abdullah Alfaidi, Aseel Mohd Zahid, Mohd Soperi Taibah University Department of Computer Science College of Computer Science and Engineering Medina Saudi Arabia Universiti Teknologi Petronas Faculty of Science IT Dept. of Computer and Info. Sciences Seri Iskandar Malaysia

ISBN: (纸本)9781728171517

In 2030 Vision for the Kingdom of Saudi Arabia, one of the most critical issues is improving the manual and traditional health clinic system that will provide faster, efficient and quality healthcare services. The objective of this study is to understand the manual system used by a university clinic in Saudi Arabia and propose an automated system to realize the benefits of e-Health that started few years ago. Utilization of Android Mobile technology for clinic management and providing of care services will improve the general efficacy of the corporation, and the efficiency of the clinic by reducing wasting time experienced by patients. It also will help to provide patient care, manage clinic staff and patient data, manage and recall info.mation encountered by the usual hospital system. We distributed a survey to collect info.mation from students and clinic employees of several universities in Saudi Arabia to develop user requirements in the system. We developed our proposed system using JAVA language in the front-end connected with the back-end software. Also, we used tools such as Hypertext Markup Language (HTML), Cascading Style Sheets (CSS), Hypertext Preprocessor (PHP), and My Structured Query Language (MySQL). This automated system provides multiple patient services and will improve the info.mation infrastructure. © 2021 IEEE.

关键词： Location based services

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81页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：