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

123 篇 会议
22 篇 期刊文献

馆藏范围

145 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

69 篇 工学
- 58 篇 计算机科学与技术...
- 44 篇 软件工程
- 15 篇 信息与通信工程
- 7 篇 电气工程
- 7 篇 生物医学工程（可授...
- 7 篇 生物工程
- 4 篇 仪器科学与技术
- 4 篇 控制科学与工程
- 3 篇 机械工程
- 3 篇 材料科学与工程（可...
- 3 篇 建筑学
- 3 篇 安全科学与工程
- 2 篇 动力工程及工程热...
- 2 篇 电子科学与技术（可...
- 2 篇 交通运输工程
- 2 篇 环境科学与工程（可...
29 篇 理学
- 20 篇 数学
- 7 篇 生物学
- 5 篇 系统科学
- 4 篇 统计学（可授理学、...
16 篇 管理学
- 12 篇 管理科学与工程(可...
- 5 篇 工商管理
- 5 篇 图书情报与档案管...
- 2 篇 公共管理
6 篇 医学
- 6 篇 临床医学
- 5 篇 基础医学(可授医学...
- 3 篇 公共卫生与预防医...
4 篇 法学
- 4 篇 社会学
2 篇 教育学
- 2 篇 教育学
2 篇 艺术学
- 2 篇 设计学（可授艺术学...
1 篇 农学

主题

14 篇 computer science
13 篇 proposals
13 篇 feature extracti...
12 篇 machine learning
10 篇 computer archite...
8 篇 optimization
7 篇 computational mo...
7 篇 internet
7 篇 databases
7 篇 genetic algorith...
6 篇 intrusion detect...
6 篇 global optimizat...
6 篇 accuracy
6 篇 training
6 篇 authorization
5 篇 application soft...
5 篇 data mining
5 篇 costs
5 篇 multi agent syst...
4 篇 conferences

机构

9 篇 graduate program...
8 篇 graduate program...
6 篇 graduate program...
5 篇 department of co...
4 篇 graduate program...
4 篇 graduate program...
4 篇 industrial and s...
4 篇 department of me...
3 篇 graduate program...
3 篇 graduate program...
3 篇 graduate program...
3 篇 graduate program...
3 篇 industrial and s...
3 篇 graduate program...
2 篇 graduate program...
2 篇 electrical engin...
2 篇 department of me...
2 篇 industrial and s...
2 篇 electrical engin...
2 篇 informatics depa...

作者

10 篇 altair o. santin
8 篇 carlos n. silla
8 篇 edson e. scalabr...
8 篇 eduardo k. viega...
7 篇 llanos carlos h.
7 篇 fabrício enembre...
6 篇 muñoz daniel m.
6 篇 enembreck fabríc...
6 篇 carlos maziero
6 篇 ayala-rincón mau...
6 篇 richardson ribei...
5 篇 leandro dos s. c...
5 篇 carlos h. llanos
5 篇 scalabrin edson ...
5 篇 stihler maicon
5 篇 ávila bráulio c.
5 篇 fabricio enembre...
5 篇 vilmar abreu
5 篇 altair olivo san...
5 篇 santin altair o.

语言

139 篇 英文
3 篇 其他
3 篇 中文

检索条件"机构=Graduate Program in Computer Science Pontifical Catholic University of Parana"

共 145 条记录，以下是1-10 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：

Passive Identification of Rogue Industrial Access Points Using a One-Class Machine Learning Model 50

Passive Identification of Rogue Industrial Access Points Usi...

引用

50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： de Paula, André L.S. Viegas, Eduardo K. Santin, Altair O. Graduate Program in Computer Science Pontifical Catholic University of Parana Brazil

ISBN: (纸本)9781665464543

Access point (AP) security has become increasingly important as wireless local area networks (WLANs) proliferate in industrial environments. Rogue APs are often used by attackers to conduct man-in-the-middle (MiTM) attacks. They can redirect users to malicious servers or do eavesdropping and manipulation of their *** this paper, we propose a novel one-class machine learning model to passively identify rogue APs in industrial environments. The implementation of the model is twofold. First, we passively extract the hardware and software characteristics of the evaluated AP according to its generated messages. This results in a comprehensive feature set that captures both low-level and high-level behaviors of the evaluated ***, we apply a one-class machine learning model to identify APs that significantly deviate from the previously known profile of legitimate APs. The combined evaluation of hardware and software behaviors integrated with an outlier detection scheme to effectively identify rogue APs is the insight of our proposal. We demonstrate the feasibility of our model, achieving an F1 score of 0.89 and a true positive rate of 0.9 in experiments conducted on our new publicly available dataset of 357 unique AP behaviors. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

A Multi-View Android Malware Detection Model Through Multi-Objective Optimization 23

A Multi-View Android Malware Detection Model Through Multi-O...

引用

23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024

作者： Fransozi, Philipe Geremias, Jhonatan Viegas, Eduardo K. Graduate Program in Computer Science Pontifical Catholic University of Parana Brazil

ISBN: (纸本)9798350374889

Over the past few years, several highly accurate Machine Learning (ML) techniques have been proposed for Android malware detection. Unfortunately, proposed schemes are rarely used in production, a situation usually caused by their limited generalization capabilities, leading to low accuracies when deployed. This paper proposes a new multi-view Android malware detection model, implemented in two stages. First, we extract multiple feature sets from an analyzed Android application package. The feature sets provide a complementary Android app behavioral vector for the classification task, enhancing the system's generalization. Secondly, we conduct a multi-objective optimization to select the optimal feature subset from each view for subsequent ensemble-based classification. Our proposal's insight is to proactively select each feature subset that simultaneously improves accuracy and reduces processing requirements in a multi-view setting. Experiments on our new dataset, comprising over 40 thousand Android app samples, demonstrated the feasibility of our proposal. Our scheme can improve true-positive rates by an average of 4.4 while demanding only up to 65% of inference processing costs. © 2024 IEEE.

关键词： Android malware

来源：评论

学校读者我要写书评

暂无评论

Towards a Feasible Palm Vein Verification Scheme Using Deep Autoencoder and Siamese Networks 23

Towards a Feasible Palm Vein Verification Scheme Using Deep ...

引用

23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024

作者： Nunes, Mateus Viegas, Eduardo K. Santin, Altair O. Pontifical Catholic University of Parana Graduate Program in Computer Science Brazil

ISBN: (纸本)9798350374889

Palm vein pattern recognition offers a unique personal identification feature. Unfortunately, these techniques typically require a Near Infrared (NIR) camera sensor to extract the individual's venous pattern, challenging their wide deployment. This paper proposes a new feasible palm vein verification scheme using a Deep Autoencoder and a Siamese Network, implemented threefold. First, we capture the individual's palm using a traditional visible spectrum camera sensor and perform preprocessing tasks to correct imprecise positioning, easing palm support accessories requirements. Second, we eliminate NIR sensor requirement by fine-tuning a Deep Autoencoder model to convert images from the visible spectrum to their infrared counterparts. Third, generated images are processed by a lightweight Siamese network using a contrastive loss function for individual verification. Experiments conducted on a publicly available dataset with over a hundred individuals confirmed the feasibility of our proposal. Our scheme reaches up to 0.97 of true-negative rate, with only 0.01 decrease compared to traditional NIR-based approaches. In addition, individual identification can be conducted in less than 6 seconds in a resource-constrained environment thanks to our lightweight model's implementation. © 2024 IEEE.

关键词： Palmprint recognition

来源：评论

学校读者我要写书评

暂无评论

Multi-step ahead wind power forecasting based on N-BEATS model

Multi-step ahead wind power forecasting based on N-BEATS mod...

引用

2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Agottani, Luis Fernando Rodrigues Girardi, Matheus Melara De Souza Chaves, Wendel Rafael De Azevedo Takara, Lucas Dos Santos Coelho, Leandro Mariani, Viviana Cocco Federal University of Parana Graduate Program in Mechanical Eng. Curitiba Brazil Pontifical Catholic University of Parana Department of Computer Science Curitiba Brazil Federal University of Parana Graduate Program in Electrical Eng. Curitiba Brazil

ISBN: (纸本)9789531842976

For wind power systems to operate successfully and efficiently, accurate forecasting is critical. The integration of large wind farms with smart grid technology mainly depend on accurate models for wind power output prediction. This study introduces a neural basis expansion approach named N-BEATS (neural basis expansion analysis for interpretable time series forecasting) for time series multi-step wind power forecasting. N-BEATS is a deep neural network architecture composed of multiple fully connected layers, arranged with both forward and backward residual connections. The performance of N-BEATS was benchmarked using classical approaches including AutoRegressive Integrated Moving Average (ARIMA), Seasonal AutoRegressive Integrated Moving Average (SARIMA), Holt-Winters, and the recurrent neural network named Long Short-Term Memory (LSTM). All models hyperparameters were tuned by Bayesian optimization. The N-BEATS model demonstrated superior forecasting scores and outperformed traditional methods in metrics such as mean absolute error and root mean square error for different forecasting horizons. © 2024 IEEE.

关键词： Wind forecasting

来源：评论

学校读者我要写书评

暂无评论

Towards a Feasible Palm Vein Verification Scheme Using Deep Autoencoder and Siamese Networks

Towards a Feasible Palm Vein Verification Scheme Using Deep ...

引用

International Conference on Machine Learning and Applications (ICMLA)

作者： Mateus Nunes Eduardo K. Viegas Altair O. Santin Graduate Program in Computer Science Pontifical Catholic University of Parana Brazil

ISBN: (数字)9798350374889

ISBN: (纸本)9798350374896

关键词： Training Performance evaluation Image synthesis Databases Autoencoders Machine learning Cameras Feature extraction Pattern recognition Proposals

来源：评论

学校读者我要写书评

暂无评论

A Multi-View Android Malware Detection Model Through Multi-Objective Optimization

A Multi-View Android Malware Detection Model Through Multi-O...

引用

International Conference on Machine Learning and Applications (ICMLA)

作者： Philipe Fransozi Jhonatan Geremias Eduardo K. Viegas Graduate Program in Computer Science Pontifical Catholic University of Parana Brazil

ISBN: (数字)9798350374889

ISBN: (纸本)9798350374896

关键词： Accuracy Costs Computational modeling Production Machine learning Feature extraction Malware Vectors Proposals Optimization

来源：评论

学校读者我要写书评

暂无评论

Passive Identification of Rogue Industrial Access Points Using a One-Class Machine Learning Model

Passive Identification of Rogue Industrial Access Points Usi...

引用

Annual Conference of Industrial Electronics Society

作者： André L. de S. Paula Eduardo K. Viegas Altair O. Santin Graduate Program in Computer Science Pontifical Catholic University of Parana Brazil

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

关键词： Wireless LAN Machine learning Network security Feature extraction Software Hardware Robustness Software reliability Servers Proposals

来源：评论

学校读者我要写书评

暂无评论

Network-based Intrusion Detection Through Image-based CNN and Transfer Learning

Network-based Intrusion Detection Through Image-based CNN an...

引用

International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Pedro Horchulhack Eduardo K. Viegas Altair O. Santin João A. Simioni Graduate Program in Computer Science Pontifical Catholic University of Parana (PUCPR) Brazil

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

Machine learning (ML) techniques for network intrusion detection is still limited in production environments despite promising results reported in the literature. Network traffic behavior exhibits considerable variability and evolves over time, requiring periodic model updates. This paper proposes a new approach to intrusion detection modeling based on CNN and transfer learning to reduce updating overhead. Its implementation is twofold. First, CNN is implemented using flow-based feature expansion derived from neural flattened hyperdimensional space. This expanded space representation contributes to a longer model lifetime and maintains system accuracy over time. Second, the required training data and computational cost are significantly reduced by performing periodic model updates based on a transfer learning approach. Experiments on a novel dataset with over 2.6 TB of data and one year of real-world network traffic demonstrate the feasibility of the proposal. Our proposal improves the average F1 score by up to 0.19 when no model updates are performed. While improving the system’s accuracy, model updates impose only 42.8% of the computational cost.

关键词： Wireless communication Accuracy Computational modeling Transfer learning Training data Network intrusion detection Telecommunication traffic

来源：评论

学校读者我要写书评

暂无评论

Protocol for a Graph Database of NTDs for Drug Repurposing 18th

Protocol for a Graph Database of NTDs for Drug Repurposi...

引用

18th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2024

作者： Giordani, André Ruiz, Duncan D. Graduate Program in Computer Science – PPGCC Pontifical Catholic University of Rio Grande do Sul – PUCRS Porto Alegre Brazil

ISBN: (纸本)9783031878725

Neglected tropical diseases (NTDs) are a significant health burden globally, contributing to 1–2% of all mortality. The quest for new pharmacological interventions for NTDs is hampered by the substantial time and financial resources required for drug development, alongside a marked disinterest from laboratories due to the geographic and economic profiles of affected regions. This study presents a novel protocol for leveraging graph database architectures to elucidate potential connections between NTDs and existing pharmaceuticals that may be repurposed for treatment. Focusing on tuberculosis as a case study, we constructed a graph database integrating comprehensive disease and drug data. By removing established links between tuberculosis and known treatments, we employed a Graph Convolutional Neural Network (Graph-CNN) algorithm to unearth previously unrecognized relationships. This computational approach not only facilitates the discovery of new drug-disease associations but also streamlines the repurposing process for existing medications. Our findings demonstrate the utility of advanced data engineering and machine learning techniques in identifying promising therapeutic candidates for NTDs, potentially accelerating the availability of effective treatments for these underserved diseases. The study’s contribution is underscored by a comparative analysis of state-of-the-art algorithms within our graph database framework, highlighting the efficacy of our protocol in the broader context of drug repurposing research. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Multi-step ahead wind power forecasting based on N-BEATS model

Multi-step ahead wind power forecasting based on N-BEATS mod...

引用

IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Luis Fernando Rodrigues Agottani Matheus Melara Girardi Wendel Rafael de Souza Chaves Lucas de Azevedo Takara Leandro dos Santos Coelho Viviana Cocco Mariani Graduate Program in Mechanical Eng. Federal University of Parana Curitiba Brazil Department of Computer Science Pontifical Catholic University of Parana Curitiba Brazil Graduate Program in Electrical Eng. Federal University of Parana Curitiba Brazil

ISBN: (数字)9798350390421

ISBN: (纸本)9798350390438

关键词： Accuracy Time series analysis Europe Wind power generation Predictive models Wind farms Smart grids Forecasting Wind forecasting Long short term memory

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15页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：