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

226 篇 会议
157 篇 期刊文献

馆藏范围

383 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

246 篇 工学
- 178 篇 计算机科学与技术...
- 159 篇 软件工程
- 87 篇 信息与通信工程
- 27 篇 电气工程
- 26 篇 电子科学与技术（可...
- 26 篇 生物工程
- 25 篇 控制科学与工程
- 14 篇 机械工程
- 11 篇 光学工程
- 11 篇 交通运输工程
- 11 篇 生物医学工程（可授...
- 11 篇 网络空间安全
- 10 篇 仪器科学与技术
- 8 篇 安全科学与工程
- 7 篇 土木工程
- 5 篇 建筑学
- 5 篇 化学工程与技术
138 篇 理学
- 99 篇 数学
- 28 篇 统计学（可授理学、...
- 24 篇 生物学
- 18 篇 系统科学
- 17 篇 物理学
- 6 篇 大气科学
56 篇 管理学
- 30 篇 图书情报与档案管...
- 28 篇 管理科学与工程(可...
- 7 篇 工商管理
13 篇 法学
- 9 篇 社会学
- 5 篇 法学
9 篇 医学
- 7 篇 临床医学
- 5 篇 基础医学(可授医学...
4 篇 教育学
4 篇 军事学
3 篇 农学
2 篇 经济学

主题

16 篇 feature extracti...
12 篇 security
11 篇 semantics
10 篇 deep learning
9 篇 optimization
9 篇 network security
8 篇 image enhancemen...
8 篇 neural networks
8 篇 computational mo...
8 篇 predictive model...
8 篇 protocols
8 篇 accuracy
7 篇 petri nets
7 篇 data models
6 篇 object detection
6 篇 wireless communi...
6 篇 analytical model...
6 篇 clustering algor...
6 篇 cloud computing
5 篇 deep neural netw...

机构

41 篇 shaanxi key labo...
37 篇 school of comput...
35 篇 school of comput...
32 篇 shaanxi key labo...
12 篇 xi'an university...
8 篇 shaanxi key labo...
7 篇 ministry of educ...
7 篇 department of co...
7 篇 school of mathem...
7 篇 college of xi'an...
6 篇 xi'an university...
6 篇 shaanxi key labo...
6 篇 school of mathem...
5 篇 shaanxi key labo...
5 篇 moe key lab for ...
5 篇 key lab of infor...
5 篇 school of comput...
5 篇 shaanxi key labo...
5 篇 school of comput...
5 篇 shaanxi key labo...

作者

33 篇 meng deyu
27 篇 yichuan wang
25 篇 xinhong hei
23 篇 wang yichuan
18 篇 wang hui-ming
18 篇 hei xinhong
16 篇 haiyan jin
14 篇 li wei
13 篇 jin haiyan
11 篇 hui-ming wang
11 篇 wenjiang ji
10 篇 wang lei
10 篇 lei zhu
10 篇 sun qindong
10 篇 wei wei
9 篇 bin wang
9 篇 xu zongben
9 篇 huang ke-wen
9 篇 shen yulong
8 篇 zhang lei

语言

362 篇 英文
18 篇 其他
4 篇 中文

检索条件"机构=Network Computing and Security Key Lab of Shaanxi"

共 383 条记录，以下是81-90 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 distributed multi-antenna space hopping transceiver technique

A distributed multi-antenna space hopping transceiver techni...

引用

2013 IEEE International Conference on Signal Processing, Communications and computing, ICSPCC 2013

作者： Zuo, Shalin Jia, Shuqiao Yin, Qinye MOE Key Lab for Intelligent Networks and Network Security School of Electronic and Information Engineering Xi'an Jiaotong University Xi'an 710049 Shaanxi China

ISBN: (纸本)9781479910274

To achieve secure wireless communications, since traditional solutions like frequency hopping spread spectrum (FHSS) technology not only are technically difficult to implement but also make the frequency resources shortage even more critical, researches on signal's energy distribution over space are conducted in this paper. The results indicate that space spectrum varies from location to location in multi-antenna transceiver wireless communications systems, which implies that space spectrum resources rather than frequency spectrum resources can be taken into account on security grounds. Based on this point of view, a distributed multi-antenna transceiver technique - 0/1 space hopping (SH) technique is proposed. According to the space hopping pattern, weights are first obtained at the target user via training without having to know the array manifold or to solve the sophisticated multichannel. Moreover, regular constellations can be obtained for direct symbol retrieving. Simulation results are presented and analyzed to evaluate the performance of our technique. © 2013 IEEE.

关键词： Radio transceivers

来源：评论

学校读者我要写书评

暂无评论

0/1 space hopping transceiver technology for transmission security based on reverse training

0/1 space hopping transceiver technology for transmission se...

引用

2013 IEEE International Conference on Signal Processing, Communications and computing, ICSPCC 2013

作者： Dong, Liuqing Zhang, Jianguo Wang, Bo Zheng, Tongxing Yin, Qinye MOE Key Lab for Intelligent Networks and Network Security Institute of Electronic and Information Engineering Xi'an Jiaotong University Xi'an 710049 Shaanxi China

ISBN: (纸本)9781479910274

In order to guarantee wireless communication security, this paper puts forward a 0/1 space hopping transceiver technology based on reverse training. Starting from the influence of multipath on wireless communications, this paper introduces space spectrum and makes a more in-depth explanation about it. Research shows complex channel environment has great effects on the signal distribution, and we can take advantage of channel characteristics to realize secure transmission in wireless communication. In reverse training, the receiver transmits training symbols to the transmitter in advance. Obtaining the channel information via reverse training, the transmitter uses the information to design the transmitted signals' weights. According to the channel reciprocity principle, demodulating signals needs channels corresponding to the designed weights, therefore the receiver can demodulate signals correctly while eavesdropper can't because he hasn't the corresponding channels, thus greatly reducing the information probability of interception. Simulation results show that under the same signal-to-noise ratio (SNR), the method can make the desired receivers maintain a very low symbol error rate (SER), while the eavesdropper keeps a high SER all the time no matter what the SNR is. © 2013 IEEE.

关键词： Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Exploration and practice on the construction of computer first-class major 16

Exploration and practice on the construction of computer fir...

引用

16th IEEE International Conference on Computer Science and Education, ICCSE 2021

作者： Li, Wei Hei, Xinhong Wang, Lei Wang, Xiaofan Xi'An University of Technology School of Computer Science and Engineering Xi'an China Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China Shaanxi University of Technology School of Mathematics and Computer Science Hanzhong China

ISBN: (纸本)9781665414685

This paper analyzes the current situation of the construction of the first-class computer major, and puts forward the construction scheme of the first-class computer major in local colleges based on the concept of outcome based education (OBE). The reform scheme of the construction of the first-class computer major is elaborated from four aspects: training objectives, curriculum system, teaching mode, and evaluation mechanism. © 2021 IEEE.

关键词： Training Computer science Knowledge engineering Problem-solving System analysis and design

来源：评论

学校读者我要写书评

暂无评论

Channel Drop Out: A Simple Way to Prevent CNN from Overfitting in Motor Imagery Based BCI 7th

Channel Drop Out: A Simple Way to Prevent CNN from Overfitti...

引用

7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021

作者： Luo, Jing Wang, Yaojie Xu, Rong Liu, Guangming Wang, Xiaofan Gong, Yijing Shaanxi Key Laboratory for Network Computing and Security Technology School of Computer Science and Engineering Xi’an University of Technology Xi’an China Shaanxi Province Institute of Water Resources and Electric Power Investigation and Design Xi’an China

ISBN: (纸本)9789811659393

With the development of deep learning, many motor imagery brain-computer interfaces based on convolutional neural networks (CNNs) show outstanding performances. However, the trial number of EEG in the training set is usually limited, and redundancy extensively exists in multiple channel EEG. Thus, overfitting often appears in CNN based motor imagery recognition model and greatly affects the performances of model. In this paper, channel drop out is proposed to address this problem by data augmentation and ensemble learning. Specifically, one of all EEG channels will be dropped and replaced by the mean signal of all EEG channels. In this way, the trial number in the training set was enlarged by channel drop out. And at the testing stage, all the EEG trials processed by channel drop out were fed to the CNN model and the average output probabilities of them were applied to determine the prediction. The experiments were conducted on two popular CNN models applied in motor imagery BCI and BCI Competition IV datasets 2a to verify the performances of the proposed channel drop out approach. The results show that average improvements provided by channel drop out in two-category or four-category motor imagery classification are 2.83% and 2.65% compared with the original CNN model. So the channel drop out approach significantly improves the performances of motor imagery based BCI. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Brain computer interface

来源：评论

学校读者我要写书评

暂无评论

A Novel Teaching Strategy Based on EduCoder Platform for C Programming Language 5th

A Novel Teaching Strategy Based on EduCoder Platform for C P...

引用

5th International Conference on Computer Science and Educational Informatization, CSEI 2023

作者： Li, Wei Hei, Xinhong Wang, Lei Wang, Yichuan School of Computer Science and Engineering Xi’an University of Technology Xi’an China Shaanxi Key Laboratory for Network Computing and Security Technology Xi’an China School of Mathematics and Computer Science Shaanxi University of Technology Hanzhong China

ISBN: (纸本)9789819994915

Experimental teaching is an important part of the C programming language course, which aims to cultivate students’ Computational thinking ability, problem solving ability and programming ability. However, the existing experimental teaching mode of the C programming language course has been criticized mainly for their: 1) it is difficult for teachers to check all students’ programs within a limited time;2) Limited computer room capacity, fixed time, and other factors make it difficult to meet the personalized requirements of students. In this paper, we put forward the construction scheme of experimental teaching of the C programming language course based on the EduCoder platform, which alleviates all the above two problems. The scheme follows the fundamental law of engineering practice ability training and constructs a LDEI practice teaching closed loop of "learning (L), doing (D), evaluation (E) and improvement (I)". Through specific cases, this paper elaborates the implementation process of this scheme in the experimental teaching of the C programming language course. Finally, a survey are conducted on 64 students from computer science and technology majors. The survey results show that the designed scheme effectively enhances the students’ Computational thinking ability and programming ability. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Prediction of miRNA family based on class-incremental learning

Prediction of miRNA family based on class-incremental learni...

引用

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Liu, Yajun Qiu, Lulu Li, Aimin Fei, Rong Li, Junhuai Wu, Fang-Xiang Xi'an University of Technology Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China Division of Biomedical Engineering Department of Mechanical Engineering Department of Computer Science Saskatoon Canada

ISBN: (纸本)9798350386226

With the development of deep sequencing, recent studies indicate that a miRNA precursor can generate multiple miRNA isoforms (isomiRs). The family prediction of canonical miRNAs and isomiRs could provide a basis for miRNA functional research. In this study, we propose a novel method for family identification of canonical miRNA and isomiRs based on incremental learning. First, a benchmark dataset is constructed by processing data based on miRNA sequences and their family annotation. Moreover, sequence embedding and RNN are used for capturing essential features and inherent dependencies within a sequence. Finally, incremental learning is applied to accommodate the continuous influx of miRNA sequencing data, enabling RNN to stay relevant and effective over time. Comparative experiments and ablation studies illustrate the effectiveness of our model, which can help to comprehensively understand miRNA's function. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

A random walk approach to selectional preferences based on preference ranking and propagation

A random walk approach to selectional preferences based on p...

引用

51st Annual Meeting of the Association for Computational Linguistics, ACL 2013

作者： Tian, Zhenhua Xiang, Hengheng Liu, Ziqi Zheng, Qinghua Ministry of Education Key Lab for Intelligent Networks and Network Security Department of Computer Science and Technology Xi'an Jiaotong University Xi'an Shaanxi 710049 China

ISBN: (纸本)9781937284503

This paper presents an unsupervised random walk approach to alleviate data sparsity for selectional preferences. Based on the measure of preferences between predicates and arguments, the model aggregates all the transitions from a given predicate to its nearby predicates, and propagates their argument preferences as the given predicate's smoothed preferences. Experimental results show that this approach outperforms several state-of-the-art methods on the pseudo-disambiguation task, and it better correlates with human plausibility judgements. © 2013 Association for Computational Linguistics.

关键词： Random processes

来源：评论

学校读者我要写书评

暂无评论

A Self-adaptive Single-Objective Multitasking Optimization Algorithm 1

引用

17th International Conference on Bio-Inspired computing: Theories and Applications, BIC-TA 2022

作者： Li, Xiaoyu Wang, Lei Jiang, Qiaoyong Li, Wei Wang, Bin The Key Laboratory of Network Computing and Security Technology of Shaanxi Province Xi’an University of Technology Xi’an710048 China The Key Laboratory of Industrial Automation of Shaanxi Province Shaanxi University of Technology Hanzhong723001 China School of Electronic and Information Engineering Ankang University Ankang725000 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Evolutionary multitasking optimization algorithms have been presented for dealing with multiple tasks simultaneously. Many studies have proved that EMTOs often perform better than conventional single-task evolutionary. Transferring knowledge plays a very important role in multitask optimization algorithms. Many existing methods transfer elite solutions between tasks to improve algorithm performance, however, these methods may or produce negative transfer if inter-task similarity is low or irrelevant. This paper presents a self-adaptive multitasking optimization algorithm, SAMTOA, to find more valuable transferred solutions between tasks. In SAMTOA, the solutions for the next generation transfer are adaptively determined based on the successful transfer solutions of the previous generation. The method can effectively reduce the probability of transferring useless solutions between tasks and effectively utilize valuable solutions in tasks to improve the efficiency of knowledge transfer between tasks. Experimental results on single-objective multitasking optimization benchmark problems indicate that SAMTOA outperforms the other the state-of-the-art EMTO algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Optimization

来源：评论

学校读者我要写书评

暂无评论

A permission generation and configuration method based on Rules and FP-Growth algorithm

A permission generation and configuration method based on Ru...

引用

2021 International Conference on networking and network Applications, NaNA 2021

作者： Zhu, Lei Zhang, Ziheng Hei, Xinhong Wang, Yichuan Yang, Ziliang Hu, Feixiong He, Ping Xi'an University of technology School of Computer Science and Engineering Shaanxi Xi'an710048 China Shaanxi Key Laboratory for Network Computing and Security Technology Shaanxi Xi'an710048 China Shenzhen Tencent Computer System Co. Ltd Shenzhen518054 China

ISBN: (纸本)9781665441582

With the development of computer technology, lots of enterprises had begun to build a data platform, and the data and its services already paly the import role in enterprises. However, the guarantee the data security is the primary task of platform, and data access control, especially the fine-grained access control model, had become an important means to enhance the security of platform. In this paper, we propose a data access permission configuration method based on rules and FP-growth. Specifically, FP-Growth algorithm is first used to obtain the frequent items and the association relations of data, which can be transformed into the enumerable permission configuration items. Then, the correspondence and frequency of data items are calculated to acquire the frequent items, the permission configuration acting on the data table columns is obtained according to the frequency of used data items. By filtering the strong association relation, the data items that are more closely related in the association relation and the corresponding data item values are finally obtained, and they are converted into the permission configuration that acts on the rows of the data table. The proposed method has been tested and verified to meet business needs, and the performance consumption is below the threshold. Moreover, it is feasible to utilize classical data mining algorithms to generate permission configuration, which has begun to apply the Blueking Data Platform. © 2021 IEEE.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

Self-Anomaly-Detection Model Training via Initialized Meta Model

Self-Anomaly-Detection Model Training via Initialized Meta M...

引用

2022 International Conference on networking and network Applications, NaNA 2022

作者： Ma, Xindi Su, Cunzhu Ma, Jianfeng Jiang, Qi Xi, Ning Gao, Sheng Xie, Kang School of Cyber Engineering Xidian University Shaanxi China School of Information Central University of Finance and Economics Beijing China Key Lab of Information Network Security Ministry of Public Security Shanghai China

ISBN: (数字)9781665461313

ISBN: (纸本)9781665461313

Anomaly detection has become a key challenge affecting the training accuracy of machine learning. Because the training data is usually collected from Internet, many noised samples will be captured and these samples can decrease the model training accuracy. However, because the abnormal samples are difficult to predict when the samples are collected, and the training samples collected may contain many unknown exception categories, and the labels of normal samples may be incorrect, in this case, it is difficult to train an anomaly detection model based on supervised learning to accurately identify the anomaly samples. In this paper, we propose a new unsupervised anomaly detection method based on BiGAN, namely Rt-BiGAN, to identify the outliers in the training data. Firstly, we propose a Bigan network initialization method based on meta-learning algorithm with a small number of normal samples. Then, a self-supervised drop training is designed to improve the detection ability of the model. Finally, we evaluate our Rt-BiGAN over real-world datasets and the simulations results demonstrate that our mechanism is effective to detect the outliers in model training data. © 2022 IEEE.

关键词： Anomaly detection

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39页 << < 5 6 7 8 9 10 11 12 13 14 > >>

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：