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

10,668 篇 会议
423 篇 期刊文献
38 册 图书
3 篇 学位论文

馆藏范围

11,132 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

8,570 篇 工学
- 7,285 篇 计算机科学与技术...
- 4,341 篇 软件工程
- 1,540 篇 信息与通信工程
- 1,044 篇 生物工程
- 1,022 篇 电气工程
- 952 篇 生物医学工程（可授...
- 721 篇 控制科学与工程
- 375 篇 机械工程
- 364 篇 化学工程与技术
- 324 篇 光学工程
- 271 篇 仪器科学与技术
- 224 篇 电子科学与技术（可...
- 217 篇 动力工程及工程热...
- 209 篇 安全科学与工程
3,209 篇 理学
- 1,740 篇 数学
- 1,145 篇 生物学
- 773 篇 统计学（可授理学、...
- 606 篇 系统科学
- 553 篇 物理学
- 342 篇 化学
1,889 篇 管理学
- 1,108 篇 图书情报与档案管...
- 877 篇 管理科学与工程(可...
- 390 篇 工商管理
1,092 篇 医学
- 916 篇 临床医学
- 588 篇 基础医学(可授医学...
- 379 篇 药学(可授医学、理...
- 202 篇 公共卫生与预防医...
- 200 篇 特种医学
277 篇 教育学
- 265 篇 教育学
268 篇 法学
- 224 篇 社会学
203 篇 农学
168 篇 经济学
21 篇 文学
10 篇 军事学
4 篇 艺术学

主题

2,530 篇 machine learning
819 篇 deep learning
420 篇 support vector m...
417 篇 feature extracti...
402 篇 data mining
284 篇 big data
284 篇 training
274 篇 data models
268 篇 neural networks
255 篇 predictive model...
221 篇 task analysis
188 篇 decision trees
187 篇 machine learning...
169 篇 forecasting
136 篇 computational mo...
130 篇 covid-19
130 篇 students
128 篇 artificial intel...
126 篇 classification
124 篇 internet of thin...

机构

49 篇 univ chinese aca...
38 篇 sun yat sen univ...
22 篇 university of ch...
21 篇 university of el...
20 篇 school of data a...
17 篇 tianjin univ col...
16 篇 school of comput...
16 篇 peng cheng lab p...
15 篇 sun yat sen univ...
14 篇 sun yat sen univ...
13 篇 college of compu...
12 篇 nanyang technol ...
12 篇 shanghai jiao to...
12 篇 univ chinese aca...
11 篇 school of comput...
11 篇 zhejiang univ pe...
11 篇 school of comput...
11 篇 chinese acad sci...
11 篇 peking univ ctr ...
11 篇 beijing univ pos...

作者

19 篇 liu yang
17 篇 zheng wei-shi
13 篇 li dan
13 篇 zhang bo
13 篇 wang wei
12 篇 wang ruixuan
11 篇 yin jian
11 篇 yang yang
10 篇 xiong gang
10 篇 yang zan
9 篇 li yang
9 篇 liu bo
9 篇 liu xin
9 篇 li zhen
9 篇 chen chen
9 篇 zhang kun
9 篇 nai wei
9 篇 wang tao
9 篇 zhang rui
8 篇 chen a.

语言

11,004 篇 英文
114 篇 其他
29 篇 中文
2 篇 西班牙文
1 篇 法文

检索条件"任意字段=2019 International Conference on Applied Machine Learning and Data Science, ICAMLDS 2019"

共 11132 条记录，以下是4991-5000 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：

Statistical analysis for detection of sensitive data using hadoop clusters 21

Statistical analysis for detection of sensitive data using h...

引用

21st IEEE international conference on High Performance Computing and Communications, 17th IEEE international conference on Smart City and 5th IEEE international conference on data science and Systems, HPCC/SmartCity/DSS 2019

作者： Adhikari, Binod Kumar Zuo, Wanli Maharjan, Ramesh Han, Xuming Amatya, Prakash Bahadur Ali, Wajid College of Computer Science and Technology Jilin University Changchun130012 China Amrit Campus Tribhuvan University Kathmandu Nepal

ISBN: (纸本)9781728120584

The omnipresence of internet technology and the advent of smart devices accumulate varieties of voluminous, viscous real-time data in a network from varieties of sources and also facilitates a way for criminal, intruders to attack the network which persuades information theft, financial loss, cyber-attack, and cyberwar. It is the major challenge for researchers to determine sensitive data from large scale real-time data so that the right action can be taken at the right time. Therefore, it is important to purpose a framework to handle massive data and to detect sensitive data from big data. In this regard, the collected data from the network are stored in cloud drives, other storage devices and then transferred to Hadoop distributed file system and processed with MapReduce processing using distributed computing concepts, machine learning algorithms, and advanced statistical methods. Statistical analytical tools like Descriptive Analysis, Regression, ANOVA, Parametric Levene's test, Pearson Correlation, and Kruskal-Wallis Test present that recent big data analytical tools are effective than the traditional method for retrieval of sensitive data from Big data. © 2019 IEEE.

关键词： learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Combining machine learning and Classical Optimization Techniques in Vehicle to Vehicle Communication Network 20th

Combining Machine Learning and Classical Optimization Techni...

引用

20th international conference on Intelligent data Engineering and Automated learning (IDEAL)

作者： Hamdan, Mutasem Hamdi, Khairi Univ Manchester Sch EEE Manchester Lancs England

ISBN: (纸本)9783030336073;9783030336066

In this paper a new optimization technique has been proposed to take the advantage of both the Hungarian Algorithm and Deep Q-learning Neural Network (DQN) to solve the frequency and power resources allocation problem in Vehicle to Vehicle (V2V) future networks. The result shows a better performance for the sum of cellular users throughput, reducing the complexity of the classical optimization methods, overcome the huge State-Action matrix in Q-learning and provides wireless environment features to approximate the Q-values.

关键词： Deep Q-learning Network Vehicle to vehicle network Reinforcement learning Radio resource management Ultra Reliable Low Latency communications Maximum weigh matching

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis of data Parallelism Technique in machine learning for Human Activity Recognition using LSTM 11

Performance Analysis of Data Parallelism Technique in Machin...

引用

11th IEEE Int Conf on Cloud Comp Technol and Sci (CloudCom) / 19th IEEE Int Conf Comp and Informat Technol (CIT) / 2019 Int Workshop on Resource Brokering with Blockchain (RBchain) / Asia-Pacific Serv Comp Conf (APSCC)

作者： Nguyen, Tri D. T. Park, Jae Ho Hossain, Md Imtiaz Hossain, Md Delowar Lee, Seung-Jin Jang, Jin Woong Jo, Seo Hui Huynh, Luan N. T. Tran Trong Khanh Huh, Eui-Nam Kyung Hee Univ Dept Comp Sci & Engn Seoul South Korea CHIENCE 100210F Ace Techno Tower 2Digital Ro 31 Gil 19 Seoul South Korea

ISBN: (纸本)9781728150116

Human activity recognition (HAR), driven by large deep learning models, has received a lot of attention in recent years due to its high applicability in diverse application domains, manipulate time-series data to speculate on activities. Meanwhile, the cloud term "as-a-service" has essentially revolutionized the information technology industry market over the last ten years. These two trends somehow are incorporating to inspire a new model for the assistive living application: HAR as a service in the cloud. However, with frequently updates deep learning frameworks in open source communities as well as various new hardware features release, which make a significant software management challenge for deep learning model developers. To address this problem, container techniques are widely employed to facilitate the deep learning software development cycle. In addition, models and the available datasets are being larger and more complicated, and so, an expanding amount of computing resources is desired so that these models are trained in a feasible amount of time. This requires an emerging distributed training approach, called data parallelism, to achieve low resource utilization and faster execution in training time. Therefore, in this paper, we apply the data parallelism to build an assistive living HAR application using LSTM model, deploying in containers within a Kubernetes cluster to enable the real-time recognition as well as prediction of changes in human activity patterns. We then systematically measure the influence of this technique on the performance of the HAR application. Firstly, we evaluate our system performance with regard to CPU and GPU when deployed in containers and host environment, then analyze the outcomes to verify the difference in terms of the model learning performance. Through the experiments, we figure out that data parallelism strategy is efficient for improving model learning performance. In addition, this technique helps to increase the sc

关键词： human activity recognition data parallelism machine learning LSTM containers

来源：评论

学校读者我要写书评

暂无评论

Can digital footprints save the physical lecture? 11

Can digital footprints save the physical lecture?

引用

11th international conference on Computer Supported Education, CSEDU 2019

作者： Heggernes, Tarjei Bergfjord, Ole Jakob Department of Business Administration Western Norway University of Applied Sciences Bergen Norway

ISBN: (纸本)9789897583674

We argue that better use of "digital footprints" (data generated from students’ learning activities) could be used to improve the traditional lecture. We point out some potentially important data sources, and briefly discuss how data from each of these sources can contribute to better learning. Finally, we argue that even if this development is possible, it will require changes – certainly changed priorities among faculty, but also probably recruitment of new types of expertise, for instance data scientists. © 2019 by SCITEPRESS – science and Technology Publications, Lda. All rights reserved

关键词： E-learning

来源：评论

学校读者我要写书评

暂无评论

Spectrum Allocation of Cognitive Radio Network Based on Improved Cuckoo Search Algorithm 19

Spectrum Allocation of Cognitive Radio Network Based on Impr...

引用

2nd international conference on Computer science and Software Engineering (CSSE)

作者： Xin, ZiYun Zhang, DaMin Chen, ZhongYun Guizhou Univ Big Data & Informat Engn Guiyang Guizhou Peoples R China

ISBN: (纸本)9781450371728

In order to effectively solve the discrete optimization problem of cognitive radio network spectrum allocation, a new binary adaptive cuckoo search (BACS) algorithm is proposed, which introduces reverse learning in the initialization stage of traditional cuckoo search (CS), it increases the diversity of the population. Second, the adaptive discovery probability balances the ability of global and local optimization. Finally, a cognitive wireless network spectrum allocation method based on binary adaptive cuckoo algorithm is proposed, and compared with the classical spectrum allocation algorithm for network benefit function and fairness. The simulation shows that BACS has better optimization ability and can be used to maximize the network benefits and fairness between users when applied to spectrum allocation.

关键词： Cognitive Radio Cuckoo Search Algorithm Differential Evolution Opposition-Based learning

来源：评论

学校读者我要写书评

暂无评论

Generative Modeling for Small-data Object Detection 17

Generative Modeling for Small-Data Object Detection

引用

IEEE/CVF international conference on Computer Vision (ICCV)

作者： Liu, Lanlan Muelly, Michael Deng, Jia Pfister, Tomas Li, Jia Univ Michigan Ann Arbor MI 48109 USA Google Cloud AI Mountain View CA USA Princeton Univ Princeton NJ 08544 USA Stanford Univ Stanford CA 94305 USA Google Mountain View CA 94043 USA

ISBN: (纸本)9781728148038

This paper explores object detection in the small data regime, where only a limited number of annotated bounding boxes are available due to data rarity and annotation expense. This is a common challenge today with machine learning being applied to many new tasks where obtaining training data is more challenging, e.g. in medical images with rare diseases that doctors sometimes only see once in their life-time. In this work we explore this problem from a generative modeling perspective by learning to generate new images with associated bounding boxes, and using these for training an object detector. We show that simply training previously proposed generative models does not yield satisfactory performance due to them optimizing for image realism rather than object detection accuracy. To this end we develop a new model with a novel unrolling mechanism that jointly optimizes the generative model and a detector such that the generated images improve the performance of the detector. We show this method outperforms the state of the art on two challenging datasets, disease detection and small data pedestrian detection, improving the average precision on NIH Chest X-ray by a relative 20% and localization accuracy by a relative 50%.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

LIA: A Label-Independent Algorithm for Feature Selection for Supervised learning 5th

LIA: A Label-Independent Algorithm for Feature Selection for...

引用

5th international conference on machine learning, Optimization, and data science (LOD)

作者： Gilboa-Freedman, Gail Patelsky, Alon Sheldon, Tal Interdisciplinary Ctr Herzliya Herzliyya Israel

ISBN: (纸本)9783030375997;9783030375980

The current study considers an unconventional framework of unsupervised feature selection for supervised learning. We provide a new unsupervised algorithm which we call LIA, for Label-Independent Algorithm, which combines information theory and network science techniques. In addition, we present the results of an empirical study comparing LIA with a standard supervised algorithm (MRMR). The two algorithms are similar in that both minimize redundancy, but MRMR uses the labels of the instances in the input data set to maximize the relevance of the selected features. This is an advantage when such labels are available, but a shortcoming when they are not. We used cross-validation to evaluate the effectiveness of selected features for generating different well-known classifiers for a variety of publicly available data sets. The results show that the performance of classifiers using the features selected by our proposed label-independent algorithm is very close to or in some cases better than their performance when using the features selected by a common label-dependent algorithm (MRMR). Thus, LIA has potential to be useful for a wide variety of applications where dimension reduction is needed and the instances in the data set are unlabeled.

关键词： machine learning Feature selection Symmetric uncertainty Supervised learning Classifiers Algorithm Community detection Louvain algorithm Performance evaluation

来源：评论

学校读者我要写书评

暂无评论

A new reinforcement learning-based framework for unbiased autonomous software systems 8

A new reinforcement learning-based framework for unbiased au...

引用

8th international conference on Modeling Simulation and applied Optimization, ICMSAO 2019

作者： Sulaimon, Ismail Abiodun Ghoneim, Ahmed Alrashoud, Mubarak Department of Software Engineering College of Computer and Information Sciences King Saud University Riyadh11543 Saudi Arabia

ISBN: (纸本)9781538676844

From the newsfeeds, the products and services advertised to us, job screening, risk analysis, facial recognition and to the results we get through search engines, human-curated algorithms sitting behind the scenes, are making these decisions. These algorithms sometimes display the choices of those who authored them. Algorithmic bias has always been a minor issue since the advent of computer software, not until now that computer algorithms are deeply rooted in our daily lives through smart devices, intelligent software solutions and Autonomous System. We are at the edge of leaving our critical decisions in the hands of these intelligent creations of ours. Whereas, the biases in the algorithms used to develop them and the biases in the data they were trained with are obviously still in existence. This research is aimed at adapting the existing bias detection mechanism to ensure fairness in the decision-making process of autonomous software systems. The final solution is in the form of a software module which provides access for auditing decision process of machine learning powered autonomous software systems. This, in turn, ensures fairness in the decision process of autonomous software systems. © 2019 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Improvement of Mathematical Problem Solving Ability Through Problem Based learning Model In applied Mathematics Course II In Industrial Engineering 1

Improvement of Mathematical Problem Solving Ability Through ...

引用

1st South Aceh international conference on Engineering and Technology (SAICOET)

作者： Rusnanda, Resky Safwandi Polytech South Aceh Merdeka StKomplek Reklamasi Pantai Tapaktuan City 23751 Indonesia

Problem based learning model is applicable in applied Mathematics II course in order to obtain better students' problem-solving skill in mathematic. In this research, one can learn the differences of student performance to solve problem by problem-based learning compared to traditional learning. Besides, observation has been done to student activities during class session. data analysis shows significant of a = 0.05 gained t(count) = 2.16 and t(Table) = 1.72 in other hand teaaat > ttabie, one can conclude that problem-based learning increase student performance in solving problem compared to those in control group in applied Mathematics II course, Study Program of Industrial Engineering Polytechnic of South Aceh. The student activity was rate at 69.64% average.

关键词： problem solving ability problem based learning applied mathematics

来源：评论

学校读者我要写书评

暂无评论

Early Detecting In-Hospital Cardiac Arrest Based on machine learning on Imbalanced data 7

Early Detecting In-Hospital Cardiac Arrest Based on Machine ...

引用

7th IEEE international conference on Healthcare Informatics (ICHI)

作者： Chang, Hsiao-Ko Wu, Cheng-Tse Liu, Ji-Han Lim, Wee Shin Wang, Hui-Chih Chiu, Shu-I Jang, Jyh-Shing Roger Natl Taiwan Univ Dept Comp Sci & Informat Engn Taipei Taiwan Natl Taiwan Univ Grad Inst Networking & Multimedia Taipei Taiwan Natl Taiwan Univ Hosp Dept Emergency Med Taipei Taiwan

ISBN: (纸本)9781538691380

In-hospital cardiac arrest (IHCA) diminish the survival rate of patients, despite most of the IHCA cases are preventable. More than 54% IHCA patient had abnormal clinical manifestation before they suffered a cardiac arrest. If appropriate steps were taken, patients' survival rate would be higher and medical expense would be decreased. This paper proposes a novel approach to detect IHCA before the event occurred. We construct two types of shifting windows (corresponding to two tasks) that allow machine learning to be applied for our dataset which is severely imbalanced. The results show that our approach can effectively handle the imbalanced dataset for detecting cardiac arrest. As the selection of performance index, we used the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC). In our experiments, the best classifier is random forest for task 1, with AUROC of 0.88. LSTM is the best for task 2, with AUPRC of 0.71 for the second task.

关键词： Cardiac arrest cardiopulmonary resuscitation imbalanced data classification machine learning prediction

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 << < 491 492 493 494 495 496 497 498 499 500 > >>

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：