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

671 篇 会议
16 篇 期刊文献
7 册 图书

馆藏范围

694 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

592 篇 工学
- 520 篇 计算机科学与技术...
- 281 篇 软件工程
- 155 篇 信息与通信工程
- 117 篇 电气工程
- 41 篇 生物医学工程（可授...
- 40 篇 生物工程
- 28 篇 控制科学与工程
- 24 篇 动力工程及工程热...
- 22 篇 化学工程与技术
- 21 篇 光学工程
- 21 篇 环境科学与工程（可...
- 20 篇 电子科学与技术（可...
- 18 篇 材料科学与工程（可...
- 15 篇 机械工程
- 12 篇 安全科学与工程
- 11 篇 建筑学
200 篇 理学
- 133 篇 数学
- 52 篇 统计学（可授理学、...
- 46 篇 生物学
- 34 篇 物理学
- 30 篇 系统科学
- 22 篇 化学
136 篇 管理学
- 88 篇 图书情报与档案管...
- 55 篇 管理科学与工程(可...
- 34 篇 工商管理
33 篇 医学
- 32 篇 临床医学
- 26 篇 基础医学(可授医学...
- 19 篇 药学(可授医学、理...
20 篇 法学
- 15 篇 社会学
14 篇 经济学
- 14 篇 应用经济学
9 篇 教育学
7 篇 农学
3 篇 文学
2 篇 军事学

主题

39 篇 big data
34 篇 data mining
27 篇 cloud computing
14 篇 data models
13 篇 internet of thin...
13 篇 soft sensors
12 篇 mapreduce
12 篇 machine learning
10 篇 deep learning
9 篇 predictive model...
9 篇 forecasting
8 篇 soft computing
8 篇 accuracy
7 篇 support vector m...
7 篇 feature extracti...
7 篇 privacy
6 篇 data security
6 篇 optimization
6 篇 data analytics
6 篇 computational mo...

机构

5 篇 taiyuan univ tec...
5 篇 beihang univ sch...
4 篇 univ chinese aca...
4 篇 cairo
4 篇 school of data a...
4 篇 nanjing univ inf...
3 篇 beijing univ pos...
3 篇 department of in...
3 篇 university of el...
3 篇 business develop...
3 篇 chongqing univ p...
3 篇 sun yat sen univ...
3 篇 chongqing univ p...
3 篇 henan univ sch c...
3 篇 department of co...
3 篇 edinburgh napier...
3 篇 south china univ...
3 篇 school of comput...
2 篇 school of inform...
2 篇 department of co...

作者

4 篇 guo shuai
3 篇 kirichek ruslan
3 篇 zaslavsky arkady
3 篇 wang ping
3 篇 hassanien aboul ...
3 篇 huang haihui
3 篇 gao yuxiang
3 篇 liu qi
3 篇 vikrant bhateja
3 篇 suresh chandra s...
3 篇 fuyong ge
3 篇 ziyi su
3 篇 liu xiaodong
3 篇 misra sanjay
3 篇 gai keke
3 篇 qiu meikang
3 篇 bera tushar kant...
3 篇 liu tao
3 篇 nagaraju j.
3 篇 zhou jiehan

语言

690 篇 英文
3 篇 其他
1 篇 中文

检索条件"任意字段=3rd International Conference on Soft Computing in Data Science, SCDS 2017"

共 694 条记录，以下是71-80 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：

A Secure and Verifiable Outsourcing Scheme for Machine Learning data 3rd

A Secure and Verifiable Outsourcing Scheme for Machine Learn...

引用

3rd international conference on Security and Privacy in New computing Environments, SPNCE 2020

作者： Li, Cheng Yang, Li Ma, Jianfeng Xidian University Xi’an Shaanxi710071 China

ISBN: (纸本)9783030669218

In smart applications, such as smart medical devices, in order to prevent privacy leaks, more data needs to be processed and trained locally or near the local end. However, the storage and computing capabilities of smart devices are limited, so some computing tasks need to be outsourced;concurrently, the prevention of malicious nodes from accessing user data during outsourcing computing is required. Therefore, this paper proposes EVPP (efficient, verifiable, and privacy-preserving), a machine learning method based on a collaboration of edge computing devices. In this solution, the computationally intensive part of the model training process is outsourced. Meanwhile, a random encryption perturbation is performed on the outsourced training matrix, and verification factors are introduced to ensure the verifiability of the results. In addition, when a malicious service node is found, verifiable evidence can be generated to build a trust mechanism. Through the analysis of theoretical and experimental data, it can be shown that the scheme proposed in this paper can effectively use the computing power of the equipment. © 2021, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Cloud-Based Smart Energy Framework for Accelerated data Analytics with Parallel computing of Orchestrated Containers: Study Case of CU-BEMS 3

Cloud-Based Smart Energy Framework for Accelerated Data Anal...

引用

3rd international conference on Advanced Information science and System, AISS 2021

作者： Saengkaenpetch, Kittipat Aswakul, Chaodit Thailand and Wireless Network and Future Internet Research Unit Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Thailand Wireless Network and Future Internet Research Unit Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Thailand

ISBN: (纸本)9781450385862

This paper proposes a practical smart energy framework for data analytic on energy management system at Chulalongkorn University, called CU-BEMS. This serves as an example of demand-sided smart energy application that copes with the challenges of big data analytic and real-time processing needs. The framework is based on the divide and conquer paradigm to accelerate data analytics with parallel computing. The workload is containerized and deployed on the Kubernetes cloud facility of our internationally collaborated IoTcloudServe@TEIN playground. With this playground, the workload scalability and portability can be achieved. Applying the proposed framework, this paper reports on a practical data log analysis to determine the wasted energy consumption. Based on the experimental result, the wasted energy consumption of the whole data set of CU-BEMS's communication research laboratory area from March 2014 to August 2017 can be computed within 81 seconds by using 32 cores running in parallel. The framework is expected to serve as a basis template for further research ongoing at CU-BEMS and smart energy applications that can be computationally enhanced by data analytic pipelining with containerized services as orchestrated by Kubernetes. © 2021 ACM.

关键词： data Analytics

来源：评论

学校读者我要写书评

暂无评论

data-Driven Prediction of Key Attributes for Tobacco Products 2021

Data-Driven Prediction of Key Attributes for Tobacco Product...

引用

3rd international conference on Big data Engineering, BDE 2021

作者： Pang, Shunpeng Hu, Ruotong Guo, Baoqi Jia, Junhua Ding, Xiangqian Yu, Shusong Department of Computer Science and Technology Ocean University of China Qingdao266100 China Qingdao New Star Software Consulting Co. Ltd Qingdao266100 China

ISBN: (纸本)9781450389426

Draw resistance of the cigarette is one of the critical attributes of tobacco products. It directly affects consumers' health and has a close relationship with the release of cigarette tar, smokes nicotine, and carbon monoxide volume. Therefore, to better monitor the cigarette draw resistance, we have developed a monitoring system for forecasting and tracking the cigarette draw resistance instead of random sampling by a manual that is time-consuming for the security inspector and low accuracy. To realize the interconnection and fusion of the multi-sensors data of the production process with the upper production process data, we used "PTC Thingworx" as an IIoT platform, and designed a cigarette data collection program for getting big and high-speed real-time production data. We performed pre-processing data work in terms of the customized time window for monitoring. We first introduce recurrent neural networks (RNNs) in the field to forecast-based multi-sensor data fusion approaches. It can be seen from the test of various metrics on datasets that the method proposed in this paper has strong robustness and generalizability. The technique can completely replace labor and has an outstanding contribution to replacing the monitors. © 2021 Association for computing Machinery.

关键词： Tobacco

来源：评论

学校读者我要写书评

暂无评论

A Panacea to soft computing Approach for Sinkhole Attack Classification in a Wireless Sensor Networks Environment 1

引用

3rd international conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2020

作者： Nwankwo, Kenneth E. Abdulhamid, Shafi’i Mohammad Ojeniyi, Joseph A. Misra, Sanjay Oluranti, Jonathan Ahuja, Ravin Federal University of Technology Minna Minna Nigeria Covenant University Ota Nigeria Shri Vishwakarma Skill University Gurgaon India

ISBN: (数字)9789811614804

ISBN: (纸本)9789811614798

Small sensor nodes with the capability to sense and process data make up a wireless sensor network (WSN). This environment has limitations of low energy, low computational power and simple routing protocols;making is susceptible to attacks such as sinkhole attack. This attack happens when the enemy node in the network camouflages as a genuine node nearest to the base station, thereby have information sent by a source node to another destination node travel through it, giving it chance to alter, drop or delay information from reaching to the base station as intended. In our paper, the research developed a sinkhole detection technique, an enhancement of ant colony optimization by including a hash table in the ant colony optimization technique to advance sinkhole attack detection and reduce fa1se alarm rate in a wireless sensor network. An increase in the detection rate of 96% was achieved and result out performed other related research works when compared and further research discussed. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Swarm intelligence

来源：评论

学校读者我要写书评

暂无评论

Lstm and gru deep learning architectures for smoke prediction system in indoor environment 3rd

Lstm and gru deep learning architectures for smoke predictio...

引用

3rd international conference on Big-data and Cloud computing, ICBDCC 2019

作者： Vejay Karthy, S. Senthil Kumar, Thangavel Parameswaran, Latha Department of Computer Science and Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9789811552847

In places where more number of people are present, it is difficult for people to escape that place during emergency situations. So, there arises a need to detect the severity of smoke as early as possible as smoke develops rapidly, and the officials must be alerted on the situation immediately. So, in this paper, we present a method that would make use of the camera feeds and take the images frame by frame to detect the presence and progress of smoke. We extract some features of smoke from the images. The features obtained are then fed into both of these models (LSTM, GRU). Both LSTM and GRU are mainly use the knowledge of previously obtained output over a period of time for prediction rather than just using only the output of the most recent layer like other RNN models. We use these two models as the data that is input to the model is a time series data. We discuss the advantages and compare the accuracy of the results obtained by using both LSTM and GRU methods. This system can be developed and used in smart spaces that would help for quicker response from officials. Since we use cameras that are already installed in a building, this eliminates the need to use sensors. © Springer Nature Singapore Pte Ltd 2021.

关键词： Smoke

来源：评论

学校读者我要写书评

暂无评论

Hard and soft skills for scrum global software development teams 20

Hard and soft skills for scrum global software development t...

引用

3rd international conference on software Engineering and Information Management, ICSIM 2020 - and its Workshop 2020 the 3rd international conference on Big data and Smart computing, ICBDSC 2020

作者： Hidayati, Anita Budiardjo, Eko K. Purwandari, Betty Faculty of Computer Science Universitas Indonesia Depok Indonesia

ISBN: (纸本)9781450376907

Scrum is considered as one of the solutions to overcome problems encountered in global software development (GSD). The skills of a Scrum team largely determine the successful implementation of Scrum in a GSD project. The present study aims to identify and rank the essential skills for Scrum GSD teams. First, we identified five hard skills and five soft skills by conducting a literature study and depth interviews with a software engineering expert. Second, these skills were arranged into a questionnaire, which was then distributed to thirty undergraduate students taking software engineering subjects. The students were considered as Scrum beginners in development teams. The questionnaire data were subsequently analyzed by ranking the importance of the skills. Next, the rankings were validated in a focus group discussion (FGD) with four practitioners, two academics, one policymaker, and one representative of a relevant professional association. All members of the FGD had at least five years of experience in Scrum GSD. In the following stage, frequency analysis was employed to achieve a consensus among the experts. After that, a round table discussion was conducted to confirm the consensus. The results show that programming is the most important hard skill, while interpersonal and communication are the most important soft skills. database expertise and leadership were identified as the least important hard and soft skills, respectively. Furthermore, the rank of these skills by importance is aligned with the nature of Scrum and GSD. Our findings can be used as a foundation to construct competencies in Scrum GSD teams. © 2020 Association for computing Machinery.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Traffic Prediction for Intelligent Transportation System using Machine Learning 3

Traffic Prediction for Intelligent Transportation System usi...

引用

3rd international conference on Emerging Technologies in Computer Engineering: Machine Learning and Internet of Things, ICETCE 2020

作者： Meena, Gaurav Sharma, Deepanjali Mahrishi, Mehul Central University of Rajasthan Department of Computer Science Ajmer Rajasthan India Swami Keshvanand Institute of Technology Department of Information Technology Jaipur Rajasthan India

ISBN: (纸本)9781728116839

This paper aims to develop a tool for predicting accurate and timely traffic flow Information. Traffic Environment involves everything that can affect the traffic flowing on the road, whether it's traffic signals, accidents, rallies, even repairing of roads that can cause a jam. If we have prior information which is very near approximate about all the above and many more daily life situations which can affect traffic then, a driver or rider can make an informed decision. Also, it helps in the future of autonomous vehicles. In the current decades, traffic data have been generating exponentially, and we have moved towards the big data concepts for transportation. Available prediction methods for traffic flow use some traffic prediction models and are still unsatisfactory to handle real-world applications. This fact inspired us to work on the traffic flow forecast problem build on the traffic data and *** is cumbersome to forecast the traffic flow accurately because the data available for the transportation system is insanely huge. In this work, we planned to use machine learning, genetic, soft computing, and deep learning algorithms to analyse the big-data for the transportation system with much-reduced complexity. Also, Image Processing algorithms are involved in traffic sign recognition, which eventually helps for the right training of autonomous vehicles. © 2020 IEEE.

关键词： soft computing

来源：评论

学校读者我要写书评

暂无评论

Health Status Recognition System for Communication Equipment Based on data Mining 3rd

Health Status Recognition System for Communication Equipment...

引用

3rd international conference on Computer science, Engineering and Education Applications, ICCSEEA 2020

作者： Peng, Yongjun Guo, Rui Wan, Anping You, Ningdong Wu, Lihua Department of Information Communication National University of Defense Technology Wuhan430010 China The PLA Rocket Force Command College Wuhan China Department of Mechanical Engineering Zhejiang University City College Hangzhou310015 China Wuhan Natural Resource and Planning Information Center Wuhan China Wuhan Institute of Digital Engineering Wuhan China

ISBN: (纸本)9783030555054

Communication equipment system is complicated, poor working conditions, high load for a long time running, the system will often appear all sorts of fault, the control system of chain reaction will lead to the whole production line to stop operation, this paper proposes a communication equipment system based on data mining health status identification system, using a comprehensive feature selection method was carried out on the working condition of data mining analysis, key parameters, the parameters that influence the stability of communication equipment as a communication equipment health assessment indicator;Communication equipment based on certain health state evaluation indexes, the working state of clustering analysis, the characteristics of the working condition of each cluster, obtain state distribution of historical condition, define history condition of running state categories;Then using ARIMA Communication equipment health algorithm opposition access module to determine the eigenvalues of the training model, predict the trend of change of parameters, with supplemental predicted state recognition. At last, the communication equipment health status recognition system is developed, and applied to the engineering practice, proves the validity and practicability of the system. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Health

来源：评论

学校读者我要写书评

暂无评论

A mobile-based framework for detecting objects using ssd-mobilenet in indoor environment 3rd

A mobile-based framework for detecting objects using ssd-mob...

引用

3rd international conference on Big-data and Cloud computing, ICBDCC 2019

作者： Sanjay Kumar, K.K.R. Subramani, Goutham Thangavel, Senthil Kumar Parameswaran, Latha Department of Computer Science and Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9789811552847

Object detection has a prominent role in image recognition and identification. Emerging use of neural networks approaches toward image processing, classification and detection for increasing amount of complex datasets. With the collection of large amounts of data, faster and more efficient GPUs and better algorithms, computers can be trained conveniently to detect and classify multiple objects within an image with high accuracy. Single-shot detector-MobileNet (SSD) is predominantly used as it is a gateway to other tasks/problems such as delineating the object boundaries, classifying/categorizing the object, identifying sub-objects, tracking and estimating object’s parameters and reconstructing the object. This research demonstrates an approach to train convolutional neural network (CNN) based on multiclass as well as single-class object detection classifiers and then utilize the model to an Android device. SSD achieves a good balance between speed and certainty. SSD runs a convolution network on the image which is fed into the system only once and produces a feature map. SSD on MobileNet has the highest mAP among the models targeted for real-time processing. This algorithm includes SSD architecture and MobileNets for faster process and greater detection ratio. © Springer Nature Singapore Pte Ltd 2021.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Provisioning Privacy and Accountability in Participatory Sensing 3

Provisioning Privacy and Accountability in Participatory Sen...

引用

3rd ISEA international conference on Security and Privacy, ISEA-ISAP 2020

作者： Thakur, Tejendrakumar Marchang, Ningrinla North Eastern Regional Institute of Science and Technology Department of Computer Science and Engineering Itanagar India

ISBN: (纸本)9781728167084

Mobile Crowd Sensing (MCS) is a cost-effective and innovative paradigm that exploits the power of the crowd by facilitating individuals with sensing and computing devices to collectively sense the physical world and share the sensed data. The goal is to extract information from the collected data to measure and map phenomena of common interest. For an MCS campaign to be successful, privacy of the participants should be preserved. At the same time, the platform should be able to fix responsibility when a dishonest participant behaves maliciously (for instance, shares falsified data). Hence, privacy and accountability are important issues which need to be provisioned in the MCS architecture. This work proposes an extension to an existing MCS architecture which takes care of both. Security analysis of the architecture is also presented. © 2020 IEEE.

关键词： Internet of things

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70页 << < 4 5 6 7 8 9 10 11 12 13 > >>

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：