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

148 篇 会议
86 篇 期刊文献
5 册 图书

馆藏范围

239 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

162 篇 工学
- 123 篇 计算机科学与技术...
- 83 篇 软件工程
- 24 篇 信息与通信工程
- 24 篇 控制科学与工程
- 14 篇 生物医学工程（可授...
- 12 篇 电气工程
- 11 篇 生物工程
- 9 篇 电子科学与技术（可...
- 8 篇 化学工程与技术
- 7 篇 机械工程
- 6 篇 土木工程
- 5 篇 材料科学与工程（可...
- 5 篇 网络空间安全
- 4 篇 动力工程及工程热...
107 篇 理学
- 71 篇 数学
- 19 篇 统计学（可授理学、...
- 17 篇 系统科学
- 16 篇 生物学
- 10 篇 物理学
- 6 篇 化学
37 篇 管理学
- 27 篇 管理科学与工程(可...
- 17 篇 工商管理
- 11 篇 图书情报与档案管...
13 篇 医学
- 11 篇 临床医学
- 10 篇 基础医学(可授医学...
- 6 篇 药学(可授医学、理...
- 5 篇 公共卫生与预防医...
7 篇 经济学
- 7 篇 应用经济学
6 篇 法学
- 6 篇 社会学
5 篇 教育学
- 5 篇 教育学
3 篇 文学
2 篇 哲学
2 篇 农学
2 篇 艺术学

主题

8 篇 artificial intel...
5 篇 support vector m...
4 篇 computer science
4 篇 reliability
4 篇 neural networks
4 篇 monitoring
4 篇 decision making
4 篇 dipper throated ...
4 篇 artificial neura...
3 篇 grey wolf optimi...
3 篇 computer archite...
3 篇 computational in...
3 篇 optimization
3 篇 decision trees
3 篇 middleware
3 篇 functional progr...
2 篇 covid-19
2 篇 fuzzy logic
2 篇 intrusion detect...
2 篇 software systems

机构

16 篇 department of sy...
10 篇 department of ap...
7 篇 department of ma...
6 篇 programming meth...
6 篇 department of co...
6 篇 computer enginee...
6 篇 computer techniq...
5 篇 department of co...
5 篇 department of co...
5 篇 department of co...
5 篇 department of co...
4 篇 school of electr...
4 篇 department of co...
4 篇 computer enginee...
4 篇 department of ap...
3 篇 department of ap...
3 篇 zuse institute b...
3 篇 university of tw...
3 篇 rwth aachen univ...
3 篇 programming meth...

作者

9 篇 maiti manoranjan
8 篇 mostafa abotaleb
8 篇 pal madhumangal
8 篇 abdelhameed ibra...
7 篇 abotaleb mostafa
5 篇 pal anita
5 篇 el-sayed m.el-ke...
5 篇 abdelaziz a.abde...
5 篇 de meuter wolfga...
5 篇 doaa sami khafag...
4 篇 choe km
4 篇 bergstra j.a.
4 篇 hayek ali
4 篇 dybjer peter
4 篇 van cutsem tom
4 篇 anita pal
4 篇 el-kenawy el-say...
4 篇 d'hondt theo
4 篇 madhumangal pal
3 篇 sarkar biswajit

语言

233 篇 英文
5 篇 其他
1 篇 中文

检索条件"机构=Department of Computer Technology and Computer Programming"

共 239 条记录，以下是31-40 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：

Ensuring the reliability of remote online monitoring systems

Ensuring the reliability of remote online monitoring systems

引用

International Conference on Information Science and Communications Technologies (ICISCT)

作者： Sergeev Alexandr Sergeev Mikhail Department of computer technology and programming Saint Petersburg State University of Aerospace Instrumentation Saint Petersburg Russia

the issue of ensuring the reliability of the functioning of global systems of remote online monitoring of the condition of patients is considered. Remote monitoring is in demand when supervision the health status of disabled people with cardiovascular diseases, pregnant women and children. It is especially in demand in the context of a pandemic and the accompanying restrictions on movement. Monitoring is carried out “transparently” for the patient, without involving him in the subtleties of the process of interaction with a medical institution, ensuring the preservation of his mobility due to the proposed concept of implementing a wearable online monitor device. The procedures of the online monitor initialization and distribution of functions in it are considered. Threats to the normal functioning of distributed systems with online monitors are presented, including existing problems of a general nature related mainly to global communications. Solutions are offered to ensure reliable operation of wearable devices as part of online monitors.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Information technology of remote monitoring and control

Information technology of remote monitoring and control

引用

2021 IEEE International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2021

作者： Mnushka, Oksana Savchenko, Volodymyr Leonov, Serhii Shaposhnikova, Olena Kharkiv National Automobile and Highway University Computer Technology and Mechatronics Department Kharkiv Ukraine Globallogic Ukraine Kharkiv Ukraine National Technical University 'Kharkiv Polytechnical Institute' Computer Engineering and Programming Department Kharkiv Ukraine

ISBN: (纸本)9781665412629

Remote monitoring of objects or technological processes is used in many industries and service-oriented companies to obtain up-to-date information about the state of things or technical processes. The article is devoted to developing, analyzing, and implementing information technology (IT) for remote monitoring. The high-level design of IT and system for its implementation is based on the IDEF0 Functional Modeling methodology that describes the system hierarchy and establishes horizontal links between various activities. The achieved results confirm the possibility of implementing the proposed technology. The results will be of interest to technical specialists involved in the development of relevant applications but also to business analysts and managers for a better understanding of modern applied information technologies. © 2021 IEEE.

关键词： Remote control

来源：评论

学校读者我要写书评

暂无评论

Data poisoning: issues, challenges, and needs

Data poisoning: issues, challenges, and needs

引用

7th IET Smart Cities Symposium (SCS 2023)

作者： Mohammad Aljanabi Alaa Hamza Omran Maad M Mijwil Mostafa Abotaleb El-Sayed M. El-kenawy Sahar Yousif Mohammed Abdelhameed Ibrahim Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science & Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Social Engineering Attacks Detection Approach

Social Engineering Attacks Detection Approach

引用

IEEE International Conference on Dependable Systems, Services and Technologies (DESSERT)

作者： Sergii Lysenko Volodymyr Vorobiov Oleksandr Bokhonko Piotr Gaj Oleg Savenko Jacek Wołoszyn Department of Computer Engineering and Information Systems Khmelnitsky National University Khmelnitsky Ukraine Silesian University of Technology Gliwice Poland Department of Computer Engineering and System Programming Khmelnitsky National University Khmelnitsky Ukraine Department of Informatics and Teleinformatics Kazimierz Pulaski University of Technology and Humanities in Radom Radom Poland

The paper focuses on the problem of technical social engineering attacks that encompass the manipulation of individuals to reveal sensitive information, execute actions, or breach security systems. These exploits frequently capitalize on human psychology, trust, and a lack of vigilance to attain unauthorized entry to networks, systems, or data. In contrast to traditional social engineering tactics that center on psychological manipulation, technical social engineering attacks employ technological means and strategies to manipulate and beguile individuals. The paper presents an attempt to detect social engineering attacks. The approach utilized four machine learning algorithms (decision tree, random forest, K-nearest neighbor, and extreme gradient boosting). The analysis is centered on data collected from network hosts, which may serve as indicators of a potential social engineering attack. The empirical results demonstrated high detection accuracy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Forecasting and modeling on average rainwater and vapor pressure in Chelyabinsk Russia using deep Learning models 6

Forecasting and modeling on average rainwater and vapor pres...

引用

6th Smart Cities Symposium, SCS 2022

作者： Abotaleb, Mostafa Makarovskikh, Tatiana Subhi, Alhumaima Ali Alkattan, Hussein Adebayo, Adelaja Oluwaseun Department of System Programming South Ural State University Chelyabinsk454080 Russia Electronic and Computer Center University of Diyala BaqubahMJJ2+R9G Iraq Information Communication and Technology Department Lagos State University Lagos102101 Nigeria

ISBN: (纸本)9781839538544

Machine learning technique is full-fledged as a boosting sector to develop modeling and forecasting of complex time series observations in the present environment. This study made an attempt to inspect the future performance of rainfall data and vapor in Chelyabinsk by using a machine learning technique. The data series is divided into a training set (60%) and a test set (40%) for model developing a validation purpose. We further developed deep learning models such as, LSTM, BILSTM, GRU and compared on the basis of ME, RMSE, MAE, MPE, MAPE, ACF1 on the training data set. For testing data set, we compared these deep learning models based on RMSE. LSTM model acts as a superior machine learning model over BILSTM and GRU in this data series. Forecasting performance of these three models significantly at par. This finding may be significant to build a strong literature of the Chelyabinsk weather's forecast, which can be helpful for policy makers and researchers. Also, we strongly believe that, this work could be used as a literature adaptation of machine learning technique for complex time series over statistical models. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Statistical tests

来源：评论

学校读者我要写书评

暂无评论

Design of Intelligent Decision Support System With Ensembled Machine Learning to Predict Students' Performance

Design of Intelligent Decision Support System With Ensembled...

引用

2024 International Conference on Communication, computer Sciences and Engineering, IC3SE 2024

作者： Deepan, S. Rajendran, Dineshkumar Dhaliwal, Navdeep Praveena, K. Lourens, Melanie Anandhi, R.J. School Of Cs & Ai Sr University Telangana Warangal India School Of Computing And Innovative Technologies British University Computer Games Design And Programming Viet Nam Lovely Professional University Phagwara India Institute Of Aeronautical Engineering Dundigal Hyderabad India Durban University Of Technology Faculty Of Management Sciences South Africa New Horizon College Of Engineering Department Of Information Science Engineering Bangalore India

ISBN: (纸本)9798350366846

Evaluating student performance is important for universities and institutions in the current student education landscape because it helps them create models that work better for students. The automation of various features related to fundamental student traits and behaviours that manage massive amounts of data efficiently processes these. To handle student records that included information about students' behaviour and how it related to their academic performance, the companies employed models of classification with mining concepts. Additionally, the quality of result classification can be substantially improved by using learning analytics and Educational Data Mining (EDM). The educational establishments are making an effort to lower the low student performance. To address this issue, numerous methods for assessing student performance have been devised, allowing the relevant faculties to intervene and enhance the final product. Three classes - Low Performance Student, Average Student, and Smart Student - were created using the K-Mean Clustering methodology for classifying student records. Features including grade point, number of deficits, student attendance, medium of education, and board of education are taken into account when classifying the data. In this case, the WEKA tool is also utilized for implementing the model and outcome assessments. © 2024 IEEE.

关键词： Decision support systems

来源：评论

学校读者我要写书评

暂无评论

A Method for Forecasting the Demand for Pharmaceutical Products in a Distributed Pharmacy Network Based on an Integrated Approach Using Fuzzy Logic and Neural Networks

A Method for Forecasting the Demand for Pharmaceutical Produ...

引用

International Conference on Intelligent and Fuzzy Systems, INFUS 2020

作者： Oglu, Alekperov Ramiz Balashirin Kizi, Isgandarova Ilhama Tarlan Information Technology and Programming Azerimed LLC BakuAZ1147 Azerbaijan Department of Computer Engineering Odlar Yurdu University BakuAZ1072 Azerbaijan

ISBN: (纸本)9783030511555

This article discusses the use of fuzzy logic and a neural network to predict the demand for pharmaceutical products in a distributed network, in conditions of insufficient information, a large assortment and the influence of risk factors. A comprehensive approach to solving forecasting problems is proposed using: the theory of fuzzy logic - when forecasting emerging and unmet needs and a neural network - if there is a lot of retrospective information about the actual sale of drugs and drugs. Using this approach to solve the problems of forecasting demand allows you to get statistics and experience. The general algorithm, mathematical interpretation and examples of forecasting the demand for pharmaceutical products in the face of uncertainty of information are given, and the general structure of the system for forecasting the demand for drugs is described. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Uncertainty analysis

来源：评论

学校读者我要写书评

暂无评论

Estimation of Potential Locations of Trade Objects on the Basis of Fuzzy Set Theory

Estimation of Potential Locations of Trade Objects on the Ba...

引用

International Conference on Intelligent and Fuzzy Systems, INFUS 2020

作者： Oglu, Alekperov Ramiz Balashirin Oglu, Salahli Vuqar Mamadali Information Technology and Programming Azerimed LLC BakuAZ1147 Azerbaijan Department of Computer Engineering Odlar Yurdu University BakuAZ1072 Azerbaijan

ISBN: (纸本)9783030511555

In the present article, we have considered the issue of selection of potential locations of trade objects as a multi-factor decision-making in the conditions of uncertainty by applying the theory of fuzzy sets. Examples were given to assess the location options of commercial enterprises and the potential location options of the facilities on these samples were assessed on the basis of a fuzzy extraction method in the notation MATLAB\Fuzzy Inferences Systems. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Analysing the Impact of COVID-19 outbreak and Economic Policy Uncertainty on Stock Markets in Major Affected Economies 6

Analysing the Impact of COVID-19 outbreak and Economic Polic...

引用

6th Smart Cities Symposium, SCS 2022

作者： Matuka, Adelajda Asafo, Shuffield Seyram Eweke, Gamaliel O. Mishra, Pradeep Ray, Soumik Abotaleb, Mostafa Makarovskikh, Tatiana Alhussan, Amel Ali Abdelhamid, Abdelaziz A. El-Kenawy, El-Sayed M. Dutta, P.K. Chowdhury, Subrata University of Macerata Department of Economics and Law Italy Niger Delta University Department of Banking & Finance Nigeria J.N.K.V.V. College of Agriculture M.P. Powarkheda India Centurion University of Technology and Management Odisha Paralakhemundi India Department of System Programming South Ural State University Chelyabinsk454080 Russia Department of Computer Sciences College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Saudi Arabia Department of Computer Science Faculty of Computer and Information Sciences Ain Shams University Egypt Department of Communications and Electronics Delta Higher Institute of Engineering and Technolog Egypt School of Engineering and Technology Amity University West Bengal Kolkata India AP Chittoor India

ISBN: (纸本)9781839538544

The covid-19 pandemic and Economic Policy Uncertainty resulting from the shutdown of production, withdrawal of investments, enforcement of lockdowns and quarantines globally, have been directly affecting stock markets worldwide. This study is thus an attempt to analyse the impact of the COVID-19 pandemic on stock market behaviour in major affected economies. Moreover, the time frame was extended by using current data which investigate the impact of the virus during the boom and the blast phase in the country's most hit by the pandemic crisis such as China, Italy, UK and US. The frequency of the data is daily, and it dates from 3 January 2020 up to 10 February 2021. The considered time framework will give a deep insight into how stock markets behave in the case of an exogenous shock. The Dickey-Fuller Augmented Unit Root Test indicates that all the variables are stationary at first difference, which is one of the main conditions to have robust result, and the ARCH-LM test for the heteroskedasticity of the residuals, which show that all the probability values are significant, rejecting the null hypothesis of no ARCH effect. Based on the results of GARCH (1,1), we conclude that the change in stock markets volatility is positive and significant in China, Italy, UK and USA. This suggests that the impacts of COVID-19 outbreak and economic policy uncertainty on Stock Markets are a significant and Homogeneous across the studied countries, and the shock on FTSE Italia All Share has the longest time to vanish which makes it the riskiest to invest during this period, while the shock on SP500 USA has the shortest time to disappear meaning that it is safest Stock Market in this study. These findings have significant implications for policymakers, institutional and individual investors and Financial Markets analysts. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Investments

来源：评论

学校读者我要写书评

暂无评论

Spectral Analysis of Neural Network Long-Term Predictions

Spectral Analysis of Neural Network Long-Term Predictions

引用

2021 International Conference on High technology for Sustainable Development, HiTech 2021

作者： Koparanov, Kiril Trifonov, Rumen Minkovska, Daniela Georgiev, Krasin Technical University of Sofia Department of Programming and Computer Technologies Sofia Bulgaria Technical University of Sofia Information Technology in Industry Sofia Bulgaria Technical University of Sofia Department of Aeronautics Sofia Bulgaria

ISBN: (纸本)9781665448734

Long-term predictions of time series is a task with multiple applications. Exploiting neural networks for such problem has not been studied enough for financial purposes. An empirical study of specific cases with real financial multivariate time series and data augmentation was performed. The results are compared for different neural network models and two datasets using standard and customized spectral evaluation metrics. © 2021 IEEE.

关键词： Spectrum analysis

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24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：