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

6,385 篇 会议
161 册 图书
46 篇 期刊文献

馆藏范围

6,592 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,754 篇 工学
- 4,178 篇 计算机科学与技术...
- 3,373 篇 软件工程
- 1,159 篇 信息与通信工程
- 762 篇 生物工程
- 562 篇 生物医学工程（可授...
- 496 篇 控制科学与工程
- 421 篇 电气工程
- 327 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...
- 242 篇 安全科学与工程
- 220 篇 化学工程与技术
- 214 篇 环境科学与工程（可...
2,078 篇 理学
- 942 篇 数学
- 831 篇 生物学
- 413 篇 物理学
- 399 篇 统计学（可授理学、...
- 278 篇 系统科学
- 223 篇 化学
1,417 篇 管理学
- 785 篇 管理科学与工程(可...
- 775 篇 图书情报与档案管...
- 514 篇 工商管理
614 篇 医学
- 580 篇 临床医学
- 554 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
209 篇 农学
- 199 篇 作物学
197 篇 经济学
- 196 篇 应用经济学
133 篇 教育学
23 篇 军事学
13 篇 文学

主题

279 篇 internet of thin...
262 篇 machine learning
251 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
129 篇 feature extracti...
122 篇 real-time system...
119 篇 blockchain
109 篇 support vector m...
108 篇 accuracy
107 篇 machine learning...
102 篇 convolutional ne...
100 篇 forecasting
97 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 university of ch...
18 篇 school of inform...
17 篇 jaipur national ...
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

6,255 篇 英文
331 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 6592 条记录，以下是4451-4460 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：

EgyHealth System: A Mobile Healthcare System Application with Android and Cloud computing 6th

EgyHealth System: A Mobile Healthcare System Application wit...

引用

6th international conference on Advanced Machine Learning technologies and Applications, AMLTA 2021

作者： Ali, Abdelmageid A. Omran, Nahla F. Alsayied, Amal A. Department of Computer Science Faculty of Computers and Information Minia University Minia Egypt Department of Computer Science Faculty of Computers and Information South Valley University Qena Egypt

ISBN: (纸本)9783030697167

Healthcare mobile applications provide better care and quality of services: maintaining patient confidentiality, managing patient records, and storing and retrieving data. Using mobile applications with the cloud computing system reduces response time to secure and treat patients’ lives and give them the best professional healthcare service. This paper presents cloud computing services in the mobile health care model that reducing the waste of time in emergency health care. The patient’s operation of the application, the mobile application, will discover the patient’s location and allow him to book the nearest medical center or specialist in some emergency cases. Once the patient makes the reservation, he will send the request for help to the medical center. This process includes pre-registering the patient online at the medical center to save Patient time registration. The proposed system we call the "EgyHealth model" allows patients to review their data, and each specialist or medical center’s experiences, book appointments, and conduct medical advice. Use their data wherever they are, regardless of location and time, and allow doctors to often contact their patients and communicate through the phone applications Portable using cloud computing and exchange of messages and photos for the accident or emergency itself. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Mobile cloud computing

来源：评论

学校读者我要写书评

暂无评论

Generalization of LSTM CNN ensemble profiling method with time-series data normalization and regularization 21

Generalization of LSTM CNN ensemble profiling method with ti...

引用

21st international conference on advances in ICT for Emerging Regions, ICter 2021

作者： Rathnayake, Disni Bawantha Perera, Pasindu Eranga, Heshan Ishwara, Manjusri University of Colombo Department of Statistics Faculty of Science Colombo Sri Lanka University of Colombo School of Computing Colombo Sri Lanka

ISBN: (纸本)9781665466837

This study concentrated on generalizing an anomaly detection method of time series data using ensemble LSTM CNN network with time series data normalization and regularization. Considering the relevant conditions must meet for time series normalization, an algorithm was proposed for time series normalization. Checking the stationarity and normality of time series data is fundamentally included in the proposed algorithm. Afterward, different types of time series data are visualized with different normalization methods, and the impact of each of these methods is discussed. Normalization techniques like Min - Max, Sigmoid and Tanh are used. When sigmoid normalization used with a dataset where the original data is almost in the range of zero to approximately one was able to normalize well. For the data which is not in the range of [0],[1] this method cannot be used since it tends to overlap data that is not available in original data. The study reveals that a smooth, non-linear sigmoid function performs a better transformation for many anomalous time series data as a normalization factor. The prediction errors of the LSTMCNNkeras (LSTM CNN ensemble neural network was implemented using Keras is called LSTMCNNkeras.) model are discussed and compared with and without proposed normalization approach. Also, the gross effect of both normalization and regularization steps to the prediction errors of the LSTMCNNkeras model is discussed. For the time series data where the range lies somewhere between 0 to 1, produced better predictions in LSTMCNNkeras model along with Sigmoid normalization and Dropout regularization techniques. The gross effect of Layer weight regularization with Tanh normalization was able to produce a foreseeable growth in the performance of LSTMCNNkeras model with more accurate predictions for many time series data. © 2021 IEEE.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Computer Software Technology Under the Background of Big data Development

Computer Software Technology Under the Background of Big Dat...

引用

international conference on Machine Learning and Big data Analytics for IoT Security and Privacy, SPIoT 2020

作者： Ying, Lv Zhifeng, Zhang Laiwu Vocational and Technical College No.1 Shanghai Street Laiwu JinanShandong271100 China

ISBN: (纸本)9783030627454

With the continuous development of science and technology in our country, big data technology is becoming more and more mature. In recent years, the application of computer software in our country is more and more extensive. As an important part of social production, it is of great significance to strengthen the research of computer software technology. Computer technology, as one of the landmark technologies in the 21st century, has a direct relationship with social production and people’s quality of life. Therefore, this paper focuses on the application of computer software technology in the era of big data, to improve the data processing capacity and strengthen the economic benefits of social production. Therefore, it is of great significance to strengthen the application of computer software technology in the era of big data. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Way Forward to Digital Society – Digital Transformation of Msmes from Industry 4.0 to Industry 5.0

Way Forward to Digital Society – Digital Transformation of ...

引用

international conference on Emerging Research in Electronics, Computer science and Technology (ICERECT)

作者： Kavita Bhatt S. Mohan Kumar School of Engineering and Technology CMR University Bangalore India

Digital Transformation is a new buzz word in industrial world which transforms the physical world into virtual space. It leverages the implementation of digital technologies to accelerate the growth of the industry/business. It refers to automation, digitalization of process, infrastructure, organization, management with the help of Industry 4.0 technologies like Cloud computing, 5G& 6G, analytics, Big data, Additive manufacturing, Artificial Intelligence, augmented reality, cyber-physical system, smart sensors, IoT Platforms, cloud computing. The field is continuously evolving and shaping the future of Medium, Small and micro industries (MSMEs). Digital Transformation (DX) provides opportunities and possibilities to MSMEs to accelerate their growth via recent disruption in technologies and its attached benefits. The industry is shifting towards virtual work from mechanized systems leveraging benefits of industry 4.0 practices like AI, big data, Intelligent network system, machine learning, strong network connection and making effective use of digital transformation. Since end users' requirements and consumption of goods keep increasing product industry 5.0 is gaining much attention which refers to the integration of Artificial Intelligence matching to the level of human capabilities. This paper discusses the evolution of industry 4 and emerging I4.0 technology, major drivers and factors impacting the implementation of I4.0 practices. It also covers the paradigm shift in how next-generation industry is getting shifted with the help of I5.0. It highlights the prospects of the development of technologies that is contributing to the transition of Industry 4.0 to Industry 5.0. This study provides a high-level overview of industry 4.0, its emergences and emerging technologies and transition from Industry 4.0 to Industry 5.0. This paper also highlights the main components of Industry 5.0 and how digital transformation can be moved from machine to human-machine collaborati

关键词： Industries Productivity Cloud computing Intelligent networks Computational modeling Transforms Big data

来源：评论

学校读者我要写书评

暂无评论

Implementation of data Mining Techniques in Healthcare

Implementation of Data Mining Techniques in Healthcare

引用

international conference on Innovative Sustainable Computational technologies (CISCT)

作者： Nirosha Veeramachaneni V. Vaishnavee Nikhil Ranjan Rashi Saxena K Vandana Sarvesh Kumar Department of CSE B V Raju Institute of Technology Narsapur Department of Artificial Intelligence and Data Science SNS College of Engineering Coimbatore Department of Computing Science and Engineering Galgotias University Greater Noida Computer Science & Engineering Koneru Lakshmaiah Education Foundation (KLEF) Hyderabad Department of CSE G L Bajaj Institute of Technology and Management Greater Noida Department of CSE BBD University Lucknow

ISBN: (纸本)9781665474177

Healthcare sector is having lots of data about various disease and newly discovered viruses and bacteria’s and so on. The data has been resided for a long at various data warehouses of each country’s healthcare department but due to lack of collaboration and employment of advanced machine learning algorithms the meaningful insights which may conclude from data research and association, remain hidden from world. Hence this paper proposes the application of various machine algorithms like linear regression and multi-layer perceptron on a target dataset which is having the attributes of related to healthcare industry. With implementation of algorithm the detection of diabetes in various areas covered in 80 attributes of selected dataset.

关键词： Industries Machine learning algorithms Computer viruses Error analysis Linear regression Medical services Diabetes

来源：评论

学校读者我要写书评

暂无评论

A Predictor-Corrector Method for Multi-objective Optimization in Fair Machine Learning

A Predictor-Corrector Method for Multi-objective Optimizatio...

引用

IEEE/ACM international Symposium on Big data computing (BDC)

作者： Sean Wang Arielle Carr Sihong Xie College of Arts & Sciences Cornell University Ithaca NY USA Computer Science & Engineering Lehigh University Bethlehem PA USA

Issues of fairness often arise in graphical neural networks used for misinformation detection. However, improving fairness can often come at the cost of reducing accuracy and vice versa. Therefore, we formulate the task of balancing accuracy and fairness as a multi-objective optimization (MOO) problem where we seek to find a set of Pareto optimal solutions. Traditional first-order approaches to solving MOO problems such as multi-gradient descent can be costly, especially with large neural networks. Instead, we describe a more efficient approach using the predictor-corrector method. Given an initial Pareto optimal point, this approach predicts the direction of a neighboring solution and refines this prediction using a few steps of multi-gradient descent. We show experimentally that this approach allows for the generation of high-quality Pareto fronts faster than baseline optimization methods.

关键词： Costs Neural networks Machine learning Pareto optimization Big data Task analysis Fake news

来源：评论

学校读者我要写书评

暂无评论

Automatic Detection of Rice Diseases using Deep Convolutional Neural Networks with SGD and ADAM

Automatic Detection of Rice Diseases using Deep Convolutiona...

引用

advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Pardeep Seelwal Alok Sharma Department of Computer Science and Applications Baba Mastnath University Rohtak India

Rice diseases are the major problem in all over the world of agriculture sector. The early detection of this disease will prevent the huge economic loss for the farmer. This paper proposes a deep learning algorithm to classify the disease in the rice plant. Images of healthy and blast disease affected leaves are taken for the proposed system. The features are extracted for the healthy and brown spot, leaf blast, hispa disease of the rice leaf. The total data set is divided for training and testing purposes. These images are processed with the proposed multi-classification method and the leaf is categorized into brown spot, leaf blast, hispa disease and healthy. In this work CNN model is employed using two different optimizers i.e. SGD and ADAM. It is found that SGD performed well as compared to ADAM for our application as the training accuracy is obtained from proposed model with ADAM optimizer is 92.04 % while with SGD produced the training accuracy 96.32 %.The proposed model capable of getting promising accuracy for healthy and brown spot, leaf blast, hispa disease of the rice using multi-classification model.

关键词： Training Deep learning Economics Computational modeling Feature extraction data models Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Stock Price Prediction using Machine Learning 3

Stock Price Prediction using Machine Learning

引用

3rd international conference on advances in computing, Communication Control and Networking, ICAC3N 2021

作者： Gangwar, Abhinav Kumar, Ayush Bijpuria, Eshikha Galgotias University Department of Computer Science and Engineering U.P Greater Noida India

ISBN: (纸本)9781665438117

In Stock Market Prediction, the aim is to predict the longer term price of the monetary stocks of an organization. The recent trend available market prediction technologies is that the use of machine learning that makes predictions supported the values of current exchange indices by coaching on their previous values. Machine learning itself employs completely different models to create expectation simpler and legitimate. The paper centers around the work of Regression and LSTM principally based Machine figuring out how to foresee stock qualities. Variables pondered region unit open, close, low, high and volume. In a financially volatile market, because the exchange, it's vital to own a really precise prediction of a future trend. as a result of the monetary crisis and marking profits it's important to possess a safe expectation of the upsides of the stocks. Anticipating a non-straight sign requirements progressed calculations of AI. The writing contains concentrates with totally extraordinary AI calculations like ANN (counterfeit neural organizations) with various element decision. The consequences of this examination can show that the algorithmic principle of grouping SVM (Support Vector Machines) with the help of highlight decision PCA (Principal part investigation) can have the accomplishment of building a benefit. © 2021 IEEE.

关键词： data Analytics

来源：评论

学校读者我要写书评

暂无评论

Classification of Date Fruits in a Controlled Environment Using Convolutional Neural Networks 6th

Classification of Date Fruits in a Controlled Environment Us...

引用

6th international conference on Advanced Machine Learning technologies and Applications, AMLTA 2021

作者： Alhamdan, Wadha S. N. Howe, Jacob M. Department of Computer Science University of London London United Kingdom

ISBN: (纸本)9783030697167

This paper explores the use of Convolutional Neural Networks in classifying images of date fruits as one of 9 varieties, creating several models with the highest achieving 97% accuracy. It contributes an original dataset of 1658 high-quality images taken in a controlled environment for use in both the computer vision and agricultural technology fields. A range of models is explored and trained, both with and without data augmentation, leading to high classification accuracy. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Based Breast Cancer Detection Using Logistic Regression

Machine Learning Based Breast Cancer Detection Using Logisti...

引用

Advanced technologies in Intelligent Control, Environment, computing & Communication Engineering (ICATIECE), international conference on

作者： Sivakumar M M. Prathyusha C. Sasikala A. Anandaraj Indirani. M Department of Computer Science and Technology Madanapalle Institute of Technology and Science Madanapalle India Department of Information Technology CVR College of engineering Telangana India Department of Computer Science and Engineering KPR institute of engineering and technology Coimbatore India Department of Computer Science and Engineering Sri Eshwar College of Engineering Coimbatore India Department of Information Technology Hindusthan college of Engineering and Technology Coimbatore India

ISBN: (纸本)9781665493970

In the medical domain, technology influence is immense, resulting in the processing of medical data electronically. Here the primary concern is security and time consumption while dealing with images. It raises the need for an automated system to retrieve and process images automatically. Medical diagnosis is a vital concept among which the diagnosis of the tedious disease has gained top attention among the research community. This paper focused on sensational breast cancer diagnosis using image processing methodologies. The most effective method of treating disease diagnosis is working with patient records in the form of mammography images. Using patient data is regarded as one of the finest input techniques for breast cancer prediction. Numerous image processing approaches were used to conduct this research and increase the image quality because determining the location and kind of breast cancers was crucial for producing an accurate outcome. The weka tool was used to evaluate this data against a trained set-in order to obtain the most accurate findings. In this work, we considered Naïve Bayes, classifiers for processing the mammogram images. The weka tool collects and processes the extracted data for further processing. The obtained results show that the performance achieved by the naïve bayes classifiers effectively works on predicting the region of breast cancer with tumors.

关键词： Image processing Receivers Machine learning Breast cancer Mammography Medical diagnosis data mining

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 << < 442 443 444 445 446 447 448 449 450 451 > >>

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：