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

1,820 篇 会议
19 篇 期刊文献
7 册 图书

馆藏范围

1,846 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,182 篇 工学
- 744 篇 计算机科学与技术...
- 450 篇 软件工程
- 216 篇 机械工程
- 162 篇 控制科学与工程
- 157 篇 信息与通信工程
- 137 篇 电气工程
- 115 篇 仪器科学与技术
- 67 篇 电子科学与技术（可...
- 49 篇 网络空间安全
- 46 篇 生物工程
- 37 篇 生物医学工程（可授...
- 29 篇 交通运输工程
- 27 篇 动力工程及工程热...
- 19 篇 光学工程
- 17 篇 建筑学
- 17 篇 安全科学与工程
- 17 篇 公安技术
260 篇 管理学
- 213 篇 管理科学与工程(可...
- 51 篇 图书情报与档案管...
- 45 篇 工商管理
206 篇 理学
- 109 篇 数学
- 41 篇 生物学
- 40 篇 系统科学
- 24 篇 物理学
- 24 篇 统计学（可授理学、...
60 篇 医学
- 41 篇 基础医学(可授医学...
- 38 篇 临床医学
- 21 篇 公共卫生与预防医...
34 篇 经济学
- 34 篇 应用经济学
26 篇 教育学
- 21 篇 教育学
22 篇 农学
15 篇 法学
10 篇 文学
10 篇 艺术学
4 篇 军事学
1 篇 哲学

主题

147 篇 cloud computing
92 篇 informatics
84 篇 computational mo...
55 篇 educational inst...
54 篇 conferences
46 篇 feature extracti...
43 篇 data mining
43 篇 servers
40 篇 computer archite...
39 篇 semantics
39 篇 data models
32 篇 monitoring
32 篇 databases
32 篇 accuracy
30 篇 big data
28 篇 software
28 篇 training
26 篇 visualization
26 篇 security
26 篇 standards

机构

25 篇 school of comput...
12 篇 department of co...
9 篇 school of inform...
9 篇 school of softwa...
9 篇 cloud computing ...
8 篇 dongguan researc...
7 篇 national institu...
7 篇 ieee beijing sec...
7 篇 faculty of engin...
6 篇 shanghai univers...
6 篇 information depa...
6 篇 school of scienc...
6 篇 department of ma...
6 篇 school of softwa...
5 篇 qingdao academy ...
5 篇 signal & informa...
5 篇 cloud computing ...
5 篇 collaborative in...
5 篇 management schoo...
5 篇 informatics cent...

作者

13 篇 gang xiong
10 篇 jing zhang
10 篇 bin sheng
9 篇 ping li
9 篇 xiaohua hu
9 篇 paulo maciel
8 篇 shangce gao
7 篇 xiwei liu
7 篇 li zhuo
7 篇 yinglin wang
7 篇 wang yinglin
7 篇 stoyanova-doyche...
7 篇 yi zhang
7 篇 jin sun
7 篇 zhou mengqi
6 篇 xiong gang
6 篇 shusaku tsumoto
6 篇 anum masood
6 篇 kris hauser
6 篇 shoji hirano

语言

1,836 篇 英文
9 篇 其他
1 篇 中文

检索条件"任意字段=2014 IEEE International Conference on Progress in Informatics and Computing"

共 1846 条记录，以下是191-200 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：

Dijkstra Algorithm Based Building Evacuation Edge computing and IoT System Design and Implementation

Dijkstra Algorithm Based Building Evacuation Edge Computing ...

引用

Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Yanping Ji Wensi Wang Wangxin Chen Liting Zhang Mengyu Yang Xiaowen Wang Faculty of Information Technology Beijing University of Technology Beijing China

ISBN: (纸本)9781665426565

Large and complex buildings built in China in recent years, such as Olympic venues, airports, and large hospitals, have brought new fire evacuation problems. Many designs are using Internet of Things (IoT) technology to enhance buildings’ perception of flames and smoke. In this paper, in addition to using IoT to improve the fire-awareness of buildings, a set of algorithms based on the Dijkstra’s shortest path method is designed to operate on the local FPGA edge computing terminal to determine the current optimal evacuation path. An IoT system with an evacuation lighting system provides an optimal route indication for people in the building. Compared with the traditional Internet of Things and cloud computing technology, this design uses FPGA near the data terminal to process and analyze the collected data in real time, which effectively improves the speed of data response and Reduced bandwidth congestion caused by massive data. Reduced power consumption of IoT. The system was tested in the office building of Beijing University of Technology, which can effectively indicate the path under different fire conditions. In the event of a fire, the evacuation algorithm can be updated every 10 seconds, and the emergency lights are updated every 5 seconds and indicate an emergency route.

关键词： Simulation Buildings Software algorithms Hardware Path planning Software Internet of Things

来源：评论

学校读者我要写书评

暂无评论

Monitoring and Controlling Phone Usage to Raise Awareness and Combat Digital Addiction 7

Monitoring and Controlling Phone Usage to Raise Awareness an...

引用

7th ieee international conference on Behavioural and Social computing, BESC 2020

作者： Potapova, Klara Cetinkaya, Deniz Liebchen, Gernot Bournemouth University Department of Computing and Informatics Poole United Kingdom

ISBN: (纸本)9781728186054

One of the defining factors in human progress is the fact how humans have adopted technology into their everyday lives. One of these technologies that has seen a tremendous increase in usage is the mobile phone. The potential overuse of a smartphone device is very easily done, with many possible bad psychological side effects. Digital addiction is a form of addiction that has become more prevalent with people due to the ever-growing technological advances that our devices have achieved. This work focuses on what could be done to assist people via a software application who either have the addiction or help prevent people from becoming addicted. This paper presents design and implementation of a mobile application to monitor and control the phone usage so that it can help combat digital addiction. The prototype implementation lets user see how much time they use on their phone as well as set some preferences. The study has been evaluated by user testing and having user feedback. © 2020 ieee.

关键词： Application programs

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Framework for Detecting Offensive Swahili Messages in Social Networks with Apache Spark Implementation

Machine Learning Framework for Detecting Offensive Swahili M...

引用

Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Francis Jonathan Dong Yang Glyn Gowing Songjie Wei School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China LeTourneau University Longview TX U.S.A

ISBN: (纸本)9781665426565

Languages morphological context varies by community. The linguistic analysis became more complex due to grammatical variations, cultural, traditional, slang, misspellings, and language variance. Many studies in sentimental analysis have focused on natural language processing and peoples opinions. Text language processing takes time, requires lots of storage space, and a fast computer to work in distributed networks. Many developers choose Hadoop and Map Reduce to process Big Data. This study developed a methodology that employs Apache Spark as a text classification processing engine since it is faster in cluster computing systems. African libraries and packages for language lemmatization and stemming are still lacking. The proposed approach was utilized to detect offensive Swahili texts in social networks. Swahili is the third most widely spoken language in Africa. Four different machine learning techniques were tested as benchmarks, with the multinomial logistic model proving to be the most effective. The evaluation measures show that the proposed machine learning framework is versatile and suitable for usage in centralized and distributed systems.

关键词： Social networking (online) Text categorization Machine learning Cluster computing Linguistics Natural language processing Libraries

来源：评论

学校读者我要写书评

暂无评论

Computer Vision for Astronomical Image Analysis

Computer Vision for Astronomical Image Analysis

引用

Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Sotiria Karypidou Ilias Georgousis George A. Papakostas MLV Research Group International Hellenic University Kavala Greece

ISBN: (纸本)9781665426565

Computer Vision (CV) is undoubtedly one of the most popular forms of Artificial Intelligence (AI) and its implementation has gained considerable ground in all aspects of our lives, from security and automotive, to the night sky observation and astronomy. In general, CV uses pattern recognition techniques for identifying objects in visual media (both static and moving images). The current archetype in CV is largely based on supervised AI, which uses large data sets of human-labelled images for training. Machine Learning (ML) and Deep Learning (DL) models in computer vision have undergone a period of extremely rapid development in recent past years; in particular for object recognition and localisation tasks. An area of study with great interest in practical applications that concerns this essay, is astronomical images analysis. However, one of the main challenges facing researchers these days is the existence of large quantities of annotated data sets, in the appropriate resolution and scale. This challenge consequently asks for huge amounts of storage and high computational power. In this paper, we systematically review and analyze different challenges faced by astronomers and continue with state-of-the-art methodologies that were conducted over the last decade.

关键词： Deep learning Training Computer vision Analytical models Visualization Image analysis Image resolution

来源：评论

学校读者我要写书评

暂无评论

Improving Neural Network Architecture Compression by Multi-Grain Pruning

Improving Neural Network Architecture Compression by Multi-G...

引用

Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Kevin Kollek Miguel Angel Aguilar Marco Braun Anton Kummert School of Electrical Information and Media Engineering University of Wuppertal Wuppertal Germany Aptiv Services Deutschland GmbH Wuppertal Germany

ISBN: (纸本)9781665426565

Pruning techniques for neural networks are applied to achieve superior model compression while maintaining accuracy. Common pruning approaches rely on single granularity (e.g., weights, channels, or layers) compression techniques and miss valuable optimization potential. This major limitation results in a sequence of obsolete layers with a small number of channels or highly sparse weights. In this paper, we present a novel pruning approach to address this issue. More precisely, in this work, a Multi-Grain Pruning (MGP) framework is proposed to optimize neural network architectures from coarse to fine in up to four different granularities. Besides the traditional pruning granularities, a new granularity is introduced on so-called blocks, which consist of multiple layers. By combining multiple pruning granularities, models can be optimized even further. We evaluated the proposed framework with VGG-19 on CIFAR-10 and CIFAR-100 as well as ResNet-56 on CIFAR-10 and ResNet-50 on ImageNet. The results show that our technique achieves from 31.9x up to 185.3x model compression rates with an accuracy drop from 0.08% up to 1.73% with VGG-19 on CIFAR-10.

关键词： Image coding Computational modeling conferences Neural networks Computer architecture informatics Optimization

来源：评论

学校读者我要写书评

暂无评论

Evaluating the Usability of a Social Storefront Business Model for Ecuadorian Millennials and Centennials

Evaluating the Usability of a Social Storefront Business Mod...

引用

Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Félix Fernández-Peña Fernando Ibarra-Torres Pilar Urrutia-Urrutia Diana Coello-Fiallos Research Group of Applied Informatics Universidad Técnica de Ambato Ambato Ecuador ESAI Business School Universidad Espíritu Santo Guayaquil Ecuador Career of Civil Engineering Universidad Técnica de Ambato Ambato Ecuador

ISBN: (纸本)9781665426565

Social media has been influencing almost all areas of human society during the last decade. Nevertheless, the lack of studies on the acceptance of a social storefront business model has been identified as a missing point in this research area. In this scenario, this paper evaluates the technology acceptance of a storefront website and its Facebook business page. The study was carried out with the participation of 520 young students of two Ecuadorian universities from the Coastal and the Andean region. A controlled experiment was designed based on the Technology Acceptance Model. After using the evaluated tools for two weeks, two surveys were conducted and 48 participants were interviewed. The results show that both, the perceived ease of use and the perceived usefulness of the analyzed tools have a positive impact on the behavioral intention of using social media for e-commerce. No significant differences were found but both, the storefront webpage and the Facebook business page, had positive acceptance among participants. Interviewed students sustained that social media play a key role for reinforcing the trustability of e-commerce initiatives in the country.

关键词： Technology acceptance model Social networking (online) conferences Computational modeling Sociology Sea measurements Electronic commerce

来源：评论

学校读者我要写书评

暂无评论

Learning progress modeling for monitoring student 5

Learning progress modeling for monitoring student

引用

5th international conference on informatics and computing, ICIC 2020

作者： Arafiyah, Ria Hasibuan, Zainal A. Budi Santoso, Harry Universitas Indonesia Faculty of Computer Science Depok Indonesia Universitas Dian Nuswantoro Faculty of Computer Science Semarang Indonesia

ISBN: (纸本)9781728180472

Monitoring the progress of students is part of the teacher's job which is very important and very time-consuming. Especially if there are many students with various subjects. This is the experience of most primary school teachers in Indonesia. One way to solve this problem is to predict student progress. In this study, the students' progress was predicted using Random Forest. The Random Forest algorithm is used because it can classify data that has incomplete attributes, which are usually found in student assessment data. The prediction model was built based on assessment data from 2 classes with 46 elementary school students in subjects: Indonesian, mathematics, SBdP (Cultural Arts and Crafts), PPKN (Pancasila and Citizenship Education), and Computers. The dataset comes from the formative and summative assessment results from 3 aspects (cognitive, psychomotor, and affective). The resulting model performance will be measured using accuracy and recall. The results showed that using a dataset of 5 subjects from 46 students, the Random Forest algorithm produced a learning progress model with 100% accuracy for training data and 94% for testing data. Meanwhile, the learning progress prediction model for each subject has 100% accuracy on training data and more than 96% on test data. © 2020 ieee.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

A Regional Data Center for Intelligent Agriculture 7

A Regional Data Center for Intelligent Agriculture

引用

7th international conference on Big Data, Knowledge and Control Systems Engineering, BdKCSE 2021

作者： Doychev, Emil Terziyski, Atanas Atanasova, Pepa Rahneva, Olga Ivanova, Vanya Stoyanova-Doycheva, Asya University of Plovdiv Faculty of Matematics and Informatics Plovdiv Bulgaria University of Plovdiv Faculty of Chemistry Plovdiv Bulgaria University of Plovdiv Department of Management and Quantitative Methods in Economics Plovdiv Bulgaria

ISBN: (纸本)9781665410427

The article presents the architecture of a regional data center for intelligent plant growing for the region of Plovdiv. The architecture of the data center and the presentation as a private data cloud are also considered. The main repositories of knowledge are discussed - relational databases, noSQL databases, and ontologies. Each type of storage is presented in the context of intelligent crop production. © 2021 ieee.

关键词： Ontology

来源：评论

学校读者我要写书评

暂无评论

A YOLOv3 and ODIN Based State Detection Method for High-speed Railway Catenary Dropper

A YOLOv3 and ODIN Based State Detection Method for High-spee...

引用

Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Man Zhang Weidong Jin Peng Tang Liang Li School of Electrical Engineering Southwest Jiaotong University Chengdu China China-ASEAN International Joint Laboratory of Integrated Transport Nanning University Nanning China

ISBN: (纸本)9781665426565

The dropper is one of the core equipment of high-speed railway catenary, and its working state affects the power supply stability of pantograph catenary system. In this paper, we propose an effective detection method of catenary dropper state based on target detection algorithm You Only Look Once (YOLOv3) and Out-of-Distribution Detector for Neural Networks (ODIN). This method uses YOLOv3 as dropper locating network to detect the dropper area in catenary. The designed dropper state classification model based on ODIN is trained by augmented dropper area images of various states, and then is applied to analyze the specific state of dropper area from the location area images which is output by dropper location network. The extensive experimental results show that YOLOv3 can accurately detect dropper. The ODIN can effectively eliminate the interference of locating errors on the classification of dropper state, and the detection performance of the dropper state classification model is significantly improved by data augmentation. On the testing set, the accuracy of dropper locating network is more than 94.1%, and the precision of dropper state classification model achieve 97.97%.

关键词： Power supplies Neural networks Object detection Interference Predictive models Rail transportation Data models

来源：评论

学校读者我要写书评

暂无评论

Big data integration design for general election in Indonesia 5

Big data integration design for general election in Indonesi...

引用

5th international conference on informatics and computing, ICIC 2020

作者： Karya, Gede Sunindyo, Wikan Danar Sitohang, Benhard Akbar, Saiful Mulyanto, Adi School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Department of Informatics Parahyangan Catholic University Bandung Indonesia Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9781728180472

The use of big-data analysis in elections in Indonesia has been started since the Governor Election of DKI-Jakarta in 2012 until the Presidential Election in 2019. However, its use is limited to using analytical sentiment to map support and predict election results using social-media data. We see that there is a great opportunity to use big data for a broader election, which is to facilitate the fulfillment of the information and analysis needs of all election stakeholders. But the main problem in using big-data is the integration of big data from various sources with a variety of different formats and large volumes, in addition to the issues of analysis and visualization. For this reason, in this paper, we propose a big-data integration design to meet the needs of elections in Indonesia. This big-data integration design was developed based on election regulations in Indonesia, knowledge of big-data, and the use of a NoSQL database to store unstructured data. The election big-data integration design that we propose includes (1) the information needs of each election stakeholder;(2) the potential for big-data in fulfilling the information needs of every election stakeholder;(3) big-data analysis architecture for elections;(4) big-data integration architecture for elections;(5) crawler architecture;and (5) technology architecture that can implement big-data integration design for elections. Currently, the implementation of this design is in progress in the P3MI-ITB research project. © 2020 ieee.

关键词： Big data

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185页 << < 16 17 18 19 20 21 22 23 24 25 > >>

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：