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

6,378 篇 会议
161 册 图书
47 篇 期刊文献

馆藏范围

6,586 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,749 篇 工学
- 4,176 篇 计算机科学与技术...
- 3,369 篇 软件工程
- 1,157 篇 信息与通信工程
- 762 篇 生物工程
- 563 篇 生物医学工程（可授...
- 497 篇 控制科学与工程
- 420 篇 电气工程
- 326 篇 动力工程及工程热...
- 267 篇 机械工程
- 254 篇 光学工程
- 251 篇 电子科学与技术（可...
- 240 篇 安全科学与工程
- 219 篇 化学工程与技术
- 214 篇 环境科学与工程（可...
2,076 篇 理学
- 942 篇 数学
- 830 篇 生物学
- 413 篇 物理学
- 399 篇 统计学（可授理学、...
- 278 篇 系统科学
- 222 篇 化学
1,415 篇 管理学
- 784 篇 管理科学与工程(可...
- 774 篇 图书情报与档案管...
- 514 篇 工商管理
615 篇 医学
- 580 篇 临床医学
- 555 篇 基础医学(可授医学...
- 331 篇 药学(可授医学、理...
- 302 篇 公共卫生与预防医...
359 篇 法学
- 266 篇 社会学
208 篇 农学
- 199 篇 作物学
197 篇 经济学
- 196 篇 应用经济学
132 篇 教育学
23 篇 军事学
13 篇 文学

主题

278 篇 internet of thin...
262 篇 machine learning
253 篇 cloud computing
230 篇 big data
219 篇 computational mo...
207 篇 deep learning
182 篇 data mining
157 篇 data models
137 篇 predictive model...
136 篇 artificial intel...
133 篇 training
130 篇 feature extracti...
122 篇 real-time system...
119 篇 blockchain
108 篇 support vector m...
107 篇 accuracy
107 篇 machine learning...
102 篇 convolutional ne...
100 篇 forecasting
96 篇 medical services

机构

54 篇 graphic era deem...
44 篇 chitkara univers...
24 篇 department of co...
24 篇 department of co...
21 篇 department of en...
19 篇 school of comput...
19 篇 teerthanker maha...
18 篇 school of inform...
17 篇 jaipur national ...
16 篇 university of ch...
16 篇 uttaranchal inst...
15 篇 fujian provincia...
14 篇 srm institute of...
14 篇 department of co...
14 篇 uttaranchal inst...
13 篇 computer science...
13 篇 school of comput...
11 篇 uttaranchal inst...
10 篇 college of compu...
10 篇 school of manage...

作者

21 篇 pant bhasker
20 篇 chang kuo-chi
13 篇 tripathi vikas
12 篇 kukreja vinay
12 篇 vinay kukreja
11 篇 jacob lija
11 篇 joshi kapil
11 篇 gangodkar durgap...
10 篇 iwendi celestine
10 篇 lourens melanie
10 篇 chu kai-chun
10 篇 sujithra m.
10 篇 alanya-beltran j...
9 篇 rajeswari d.
9 篇 chang fu-hsiang
9 篇 singh rajesh
8 篇 kapil joshi
8 篇 kapila dhiraj
8 篇 pavithra g.
8 篇 sanjay misra

语言

6,396 篇 英文
184 篇 其他
15 篇 中文

检索条件"任意字段=International Conference on Advances in Data Science and Computing Technologies, ASDC 2022"

共 6586 条记录，以下是4771-4780 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：

Alzheimer's disease Diagnosis from MRI using Siamese Convolutional Neural Network

Alzheimer's disease Diagnosis from MRI using Siamese Convolu...

引用

Advancements in Smart, Secure and Intelligent computing (ASSIC), international conference on

作者： K. Swetha E. N. Vijaya Kumari Ajmeera Kiran Keerthana Sree Arrola Department of Computer Science and Engineering MLR Institute of Technology Hyderabad India

AD is a neurological illness. It ranks as the sixth most common reason for both morbidity and mortality. Alzheimer's disease can progress through three stages: mild, moderate, and severe. A timely diagnosis can assist in the provision of necessary therapy, so preventing additional harm to brain tissue. Recent research has utilised technology in an attempt to diagnose Alzheimer's disease; nevertheless, the majority of machine detection technologies are inborn. The early stages of Alzheimer's disease can be diagnosed, but it is not possible to anticipate the progression of the disease. Prediction is only possible before dementia sets in. Deep Learning (DL) has the potential to detect Alzheimer's disease in its early stages. In this article, we use two different kinds of data to predict disease categories: csv data that includes cognitive task parameters like SES, MMSE, CDR, eTIV, nWBV, ASF, delay, heredity, MOCA, SAGE, CDT; and basic patient information like gender, age, dominant hand, Education, drowsiness, and visits. The csv data includes cognitive task parameters like SES, MMSE, CDR, eTIV Calculations are done to determine the F1 score, precision, recall, and accuracy of each technique.

关键词： Deep learning Brain Magnetic resonance imaging Education Medical treatment Delays Medical diagnosis

来源：评论

学校读者我要写书评

暂无评论

Diseases Prediction from Officially Anonymized Medical and Healthcare Big data

Diseases Prediction from Officially Anonymized Medical and H...

引用

IEEE international conference on Big data

作者： Hiroaki Kikuchi Satoshi Ito Kazuki Ikegami Shota Shindo School of Interdisciplinary Mathematical Sciences Meiji University Tokyo Japan Faculty of Business and Commerce Aichi Gakuin University Nagoya Japan Graduate School of Advanced Mathematical Science Meiji University Tokyo Japan

ISBN: (数字)9781665480451

ISBN: (纸本)9781665480468

With the advanced technologies for ubiquitous computing, the large sensitive big data is valuable to explore the associations of data for epidemiology. New data privacy regulations allow sharing anonymization of data for relatively low cost than that of the conventional cohort studies. In this paper, We analyze the disease risk using Anonymously Processed Information to predict the diseases risk using the anonymously processed information of medical examination and health insurance claim data consisting of 200,000 and 290,000 individuals. We aim to demonstrate that using Anonymously Processed Information should be an additional methodology to accompany conventional cohort data analysis. We analyze a diseases risk by performing a logistic regression and calculating the relative risk, and develop some machine-learning models that predict the likelihood of a disease in three years, given an individual medical examination. Finally, we reveal the reduction in accuracy of the analysis as a result of $k$ -anonymizing data.

关键词： data privacy Costs Insurance Machine learning Big data Predictive models Ubiquitous computing

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligent Management for Internet of Things: A Review

Artificial Intelligent Management for Internet of Things: A ...

引用

Current Research in Engineering and science Applications (ICCRESA), international conference on

作者： Rusul H. Altaie Haider K. Hoomod Department of Software University of Babylon Babylon Iraq Department of Computer Science Mustansiriyah University Baghdad Iraq

Nowadays, advances in communication technologies and information processing have formed the Internet of Things. The Internet of Things (IoT) is a technology that is used to send and receive the data of sensors by the use of the internet. The Internet of Things concept has developed in new fields of technology. Because the rapid developments of data carry novel challenges for IoT, the data is a huge artificial intelligence with Internet of Things systems that make managing these data more efficient to store them on the internet of things and protect it from intruders. Combining internet of thing technology with intelligent management has significant study in different areas. Machine learning and fuzzy logic are the most widely used in a broad application of the Internet of Things. This paper introduces the developments of artificial intelligence (AI) and the Internet of Things (IoT). Also, this study highlights the challenges of using artificial intelligence in the IoT that address difficulties for different applications. This article displays the meaning and importance of artificial intelligence and some applications and benefits of artificial intelligence and the Internet of Things. Also, we show the related works of AI and IoT. In the future, it was found through previous studies that the integration of artificial intelligence with the Internet of Things can be used in many areas, in addition to protecting data and institutions from hackers and natural disasters such as fire, flood, theft, etc. via security methods and techniques of artificial intelligence.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Approach for Student Academic Performance Prediction 8th

Machine Learning Approach for Student Academic Performance P...

引用

8th international conference on Frontiers of Intelligent computing: Theory and Applications, FICTA 2020

作者： Rai, Sachin Shastry, K. Aditya Pratap, Surendra Kishore, Saurav Mishra, Priyanka Sanjay, H.A. Department of Information Science and Engineering Nitte Meenakshi Institute of Technology Bengaluru India

ISBN: (纸本)9789811557873

The assessment in outcome-based learning is very vital. A significant approach toward measuring the student performance is required. Nowadays, the amounts of data that are stored in educational database are increasing rapidly. At any point of time, the institutions face various problems. One is the poor performance of the student. Second one is the exit of a student due to the complexity of curriculum, financial problems, psychological problems, lack of support, etc. To handle these issues, machine learning can be utilized. Considerable work has been done to measure the student’s performance by using different methodologies and modern technologies. In this work, the machine learning (ML) algorithms have been implemented on the student dataset of a university to predict the student’s performance. Based on the analysis of the result, it has been concluded that accuracy of the random forest (RF) classifier is more than the other classification method such as support vector machine (SVM). © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Tropical Cyclone Predicting System Model based on Ensemble Learning

Tropical Cyclone Predicting System Model based on Ensemble L...

引用

international conference on Computational science and Technology (ICCST)

作者： P. Kirubanantham A. Saranya D. Senthil Kumar Department of Computing Technologies SRM Institute of Science and Technology Chennai India Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India Department of Information Technology Sri Sai Ram Engineering College Chennai India

ISBN: (纸本)9781665476560

Every year, tropical cyclones cause a great deal of devastation and loss of life and property. Traditional strategies for forecasting tropical cyclone tracks pose various problems in terms of forecast reliability and precision as vast quantities of meteorological and tracking data continue to accumulate, Machine learning techniques have recently been competent enough to work with spatial and temporal features from a lot of data while being extremely efficient and accurate for forecasting data in big structures. Ensemble learning is a method of creating and combining several different models to solve a particular computational problem getting the highest precision. An ensemble can perform better and is able to make better predictions with better performance compared to a single model. The existing model uses the Numerical Weather Prediction (NWP) Model with Sanders Barotropic technology, deep learning applied with Convolutional Neural Network, and GRU using a dataset consisting of actual past hurricanes and cyclones occurring in the years 1945 to 2015, where the complex correlation of meteorological variables is not considered. Hence, we proposed, Boosting Tropical Cyclone Prediction Efficiency Through Time Series Analysis using an Ensemble Learning Approach. Hereby enabling support for Auto Correlation Analysis and reducing the dimension of input variables by removing irrelevant noise data. Ensemble Analysis is done efficiently in this use case giving us better prediction accuracy. The proposed system predicts cyclone status using real-world meteorological variables improving the overall accuracy and precision

关键词： Tropical cyclones Scientific computing Computational modeling Time series analysis Weather forecasting Predictive models Numerical models

来源：评论

学校读者我要写书评

暂无评论

Ongoing advancement of free-moving radiation imaging and mapping 24

Ongoing advancement of free-moving radiation imaging and map...

引用

conference on Hard X-Ray, Gamma-Ray, and Neutron Detector Physics XXIV

作者： Quiter, Brian J. Bandstra, Mark S. Cates, Joshua W. Cooper, Reynold J. Curtis, Joseph C. Hellfeld, Daniel Joshi, Tenzing H. Y. Pavlovsky, Ryan T. Rofors, Emil Salathe, Marco Vavrek, Jayson R. Vetter, Kai Lawrence Berkeley Natl Lab 1 Cyclotron Rd Berkeley CA 94720 USA Univ Calif Berkeley CA USA

ISBN: (纸本)9781510654662

By combining radiation detection technologies with robotics sensing, the ability to continuously conduct gamma-ray imaging using freely-moving systems was demonstrated in 2015.(1) This new method, which was named free-moving 3D Scene data Fusion (SDF), was then applied to mapping radioactive contamination and to contextualizing the extent of contamination and the efficacy of radiological clean-up efforts.(2, 3) Since then, further studies into the types of radiation detection systems to which SDF could be applied resulted in the discovery and demonstration that neutron activity could be mapped using neutron-sensitive CLLBC scintillators, arrays of pixelated CZT detectors could be used to create multi-modal imagers, and more rudimentary detector systems such as arrays of four CsI modules could still achieve good-quality mapping by inferring source positioning through the encoded modulation of source-to-detector distance. This paper provides an overview of the SDF technology, highlights recent measurements leveraging SDF-equipped systems, discusses the continued development of quantitative algorithms(4, 5) and their ramifications for developing autonomous SDF-capabilities, and summarizes future directions of research and application development for free moving radiation detection systems.

关键词： Radiation imaging robotics SPIE Scene data Fusion

来源：评论

学校读者我要写书评

暂无评论

The ICT Design for Modern Education Technology and Applications

The ICT Design for Modern Education Technology and Applicati...

引用

Future technologies conference, FTC 2020

作者： Svetsky, Stefan Moravcik, Oliver Mikulowski, Dariusz Shyshkina, Mariya Faculty of Materials Science and Technology of Slovak University of Technology Bratislava Slovakia Faculty of Sciences Siedlce University of Natural Sciences and Humanities Siedlce Poland Institute of Information Technologies and Learning Tools of NAES of Ukraine Kiev Ukraine

ISBN: (纸本)9783030630911

The current trend towards automation and data exchange in manufacturing technologies, known as Industry 4.0, has also an impact on engineering education. This has a significant influence on the field of research on information communication technology (ICT) for education. It means that the digitalization of teaching processes requires not only suitable supporting software tools but also a suitable infrastructure for managing the flow and transmission of educational knowledge within this infrastructure (clouds, remote desktops, virtual spaces, personal computers). In this context, the authors aim to fill a gap in universal ICT support for teaching, and the state of the art in ICT in general. This gap involves reassessing the actual issues in modern education technology and applications, and requires a more universal approach, because global software or cloud and Web services are not automatically suitable solutions for use in personalized teaching situations where the key players are teachers, i.e. individuals. An approach (also supported within the international research Consortium V4+ACARDC), is illustrated by examples such as testing clouds (cloud content management), virtual spaces, and the development of educational packages and supporting software for visually impaired people. © 2021, Springer Nature Switzerland AG.

关键词： Knowledge management

来源：评论

学校读者我要写书评

暂无评论

Predicting Online Game-Addicted Behaviour with Sentiment Analysis Using Twitter data 2nd

Predicting Online Game-Addicted Behaviour with Sentiment Ana...

引用

2nd international conference on Machine Learning, advances in computing,Renewable Energy and communication, MARC 2020

作者： Narwal, Ramesh Aggarwal, Himanshu Computer Science & Engineering Department Punjabi University Patiala147002 India

ISBN: (纸本)9789811623530

Social media give us the power to connect and share our views with millions of people;it does not matter how far away they are. Before social media, it is not an easy task to connect with millions of people. The Internet plays a vital role in this journey. Even a lot of development was done in the field of games. Like social media, people can communicate with each other;it does not matter how far away they are. People can play online games with others;it does not matter how much far away they are. The top 10 online games are Fortnite, PUBG, Overwatch, Apex Legends, Minecraft, Dota 2, Grand Theft Auto V, League of Legends, Sea of Thieves, Counter-Strike: Global Offensive (Top 10 Online Multiplayer Games | Game Development | Melior Games, https://***/game-development/top-10-online-multiplayer-games/. Accessed 20 October 2020, [1]). Sometimes, the government took some steps regarding these online games or apps. Like the Government of India (GoI) banned 118 mobile apps regarding privacy concerns of its people (India bans 118 more Chinese mobile apps including PUBG Mobile over privacy concerns—The Financial Express, https://***/industry/technology/india-bans-118-more-chinese-mobile-apps-including-pubg-mobile-over-privacy-concerns/2072830/. Accessed 20 October 2020). PUBG, a popular online game, is one of them that is forbidden by GoI. So, people expressed their views on Twitter and other social media. In this paper, we download tweets regarding PUBG;sentiment analysis was done using lexical analysis and machine learning techniques. We classify tweets in three factors like neutral, negative, and positive. Most of the persons who are posting negative comments mean they are using PUBG, and they are addicted. We are trying to find online gaming addictive behaviour of people. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Expression of Concern for: Heart Attack Prediction using Machine Learning

Expression of Concern for: Heart Attack Prediction using Mac...

引用

international conference on Inventive Research in computing Applications (ICIRCA)

作者： Janaraniani N Divya P Madhukiruba E R. Santhosh R. Reshma D. Selvapandian Department of Computer Science and Engineering Karpagam Academy of Higher Education Coimbatore

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497084

In the recent years, the coronary artery disease (CAD) becomes leading cause of mortality worldwide both in high-income nations and in poor countries to a rising extent. Studies of human genetics can provide useful information for the development of such enhanced techniques by enhancing our ability to identify those who are at a higher risk for CAD. This work explores artificial intelligence technologies that analyze raw clinical data for the study and assessment of heart disease severity. Further utilizes machine learning algorithms to predict various state of CAD in individuals, such as naive bayes (NB), decision tree (DT), and Weighted Associative Rule Mining (WARM). This research study has tested these algorithms on the clinical data obtained from the Cardiology department, which include highlights and distinct cases. The decision tree achieves the highest prediction accuracy of 99.5 percent with the fastest rate of exactness over other algorithms.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Hybrid Music Recommendation System Utilizing Item Popularity and Content-Based Filtering Innovations in music

Hybrid Music Recommendation System Utilizing Item Popularity...

引用

data science, Agents & Artificial Intelligence (ICDSAAI), international conference on

作者： Aditya Singh Utsav Porwal P. Selvaraj Department of Computing Technologies College of Engineering and Technology Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur India

ISBN: (纸本)9798350333855

recommendation systems are increasing, making it viable to customize the listening trends and fine-tune the selections per the user’s preferences. Over the years, every user’s personalized music playlist can be primarily customized based totally on the statement of that user’s behavior. In this work, we advocate a Hybrid Music advice machine using object recognition and content analysis primarily based on innovative filtering. We illustrated its implementation for virtual audio, a product class with swiftly increasing trends. The proposed machine routinely indicates customized playlists of MP3 songs for every user. The machine works in real-time and is scalable to the significant statistics generally encountered in personalization applications. We applied this personalization system on the "Million-Song dataset" and examined its overall performance with several users. Moreover, our proposed recommendation system performs well in recommending the music based on the item’s popularity and user-centric content filtering.

关键词： Technological innovation Filtering Market research Real-time systems Behavioral sciences Object recognition Artificial intelligence

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 << < 474 475 476 477 478 479 480 481 482 483 > >>

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：