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

477 篇 会议
78 篇 期刊文献
10 册 图书

馆藏范围

565 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

344 篇 工学
- 277 篇 计算机科学与技术...
- 239 篇 软件工程
- 109 篇 信息与通信工程
- 50 篇 控制科学与工程
- 38 篇 电气工程
- 33 篇 生物工程
- 28 篇 电子科学与技术（可...
- 25 篇 安全科学与工程
- 21 篇 交通运输工程
- 20 篇 动力工程及工程热...
- 18 篇 生物医学工程（可授...
- 17 篇 机械工程
- 13 篇 网络空间安全
- 10 篇 光学工程
- 10 篇 仪器科学与技术
- 10 篇 化学工程与技术
140 篇 理学
- 80 篇 数学
- 37 篇 生物学
- 27 篇 统计学（可授理学、...
- 25 篇 物理学
- 25 篇 系统科学
- 11 篇 化学
95 篇 管理学
- 64 篇 管理科学与工程(可...
- 41 篇 图书情报与档案管...
- 36 篇 工商管理
27 篇 法学
- 19 篇 社会学
21 篇 医学
- 19 篇 临床医学
- 18 篇 基础医学(可授医学...
- 13 篇 公共卫生与预防医...
11 篇 经济学
- 11 篇 应用经济学
8 篇 教育学
4 篇 农学
3 篇 文学
2 篇 军事学

主题

19 篇 security
15 篇 real-time system...
14 篇 computational mo...
14 篇 protocols
13 篇 accuracy
13 篇 training
13 篇 convolutional ne...
12 篇 authentication
11 篇 wireless sensor ...
11 篇 feature extracti...
11 篇 artificial intel...
10 篇 neural networks
10 篇 machine learning
9 篇 optimization
9 篇 data mining
9 篇 servers
9 篇 data models
8 篇 deep learning
8 篇 wireless communi...
8 篇 predictive model...

机构

6 篇 dept. of automat...
6 篇 ufa state aviati...
6 篇 dept. of softwar...
5 篇 dept. of automat...
4 篇 dept. of compute...
4 篇 dept. of compute...
4 篇 networking and i...
4 篇 cyber security s...
4 篇 dept. of informa...
4 篇 dept. of compute...
4 篇 sri lanka instit...
3 篇 dept. of electri...
3 篇 the hashemite un...
3 篇 dept. of compute...
3 篇 dept. of compute...
3 篇 national univers...
3 篇 dept. of digital...
3 篇 dept. of compute...
3 篇 saic motor ai la...
3 篇 max planck insti...

作者

6 篇 nikumani choudhu...
6 篇 vulfin alexey
5 篇 xi zhang
5 篇 nataliia zaiets
5 篇 lidiia vlasenko
5 篇 nataliia lutska
5 篇 farkas csilla
5 篇 jong-hyouk lee
4 篇 wijesekera dumin...
4 篇 chen bing
4 篇 vlasenko lidiia
4 篇 lee jong-hyouk
4 篇 sarantoglou geor...
4 篇 zaiets nataliia
4 篇 v. sreejith
4 篇 weng jian
4 篇 lutska nataliia
4 篇 lee hoon jae
4 篇 koushik reddy ch...
4 篇 mesaritakis char...

语言

550 篇 英文
12 篇 其他
2 篇 中文
1 篇 日文

检索条件"机构=Dept. of Computer and Network Engineering Dept. of Information Systems and Security"

共 565 条记录，以下是91-100 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：

Selfish Users in Listen-Before-Talk Co-existence of Cellular-Wi-Fi networks: Counteraction Methods

Selfish Users in Listen-Before-Talk Co-existence of Cellular...

引用

International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless networks (WiOpt)

作者： Saibharath S Sudeepta Mishra Gazal Arora Anamika Sharma Chittaranjan Hota Dept. of Computer Science and Information systems BITS Pilani Hyderabad Campus India Dept. of Computer Science and Engineering IIT Ropar Punjab India

5G operates in the unlicensed spectrum to expand its capacity. This spectrum provides more uplink and downlink frequency bands in 5G to satisfy ultra-dense and scalability requirements. Wi-Fi is a prominent wireless technology that operates in unlicensed bands. Due to the proximity of cellular and Wi-Fi channels, utilization of both Wi-Fi and 5G New Radio (NR) can cause interference. The co-existence of 5G NR and Wi-Fi devices lacks the means of communication for negotiation and coordination among them. Listen-Before-Talk and Duty-cycling are standard Medium Access Control (MAC) mechanisms to enable co-existence. Due to a lack of coordination, network utilization becomes unfair with the existence of selfish devices. The selfish users could maximize throughput and affect other Wi-Fi and NR users. Here, we investigate the effects of selfish nodes on this Wi-Fi Co-existence with 5G. These nodes disobey exponential backoff to boost their channel acquisition. We study the effect of misbehavior through the Order Gain metric. Through standard CSMA/CA settings with overall channel occupancy of 99.75%, we demonstrate that selfish users profoundly impact fair co-existence. We study the side effects through throughput, channel sensing, and acquisition for various backoff window access patterns. Finally, we go through counteraction methods to overcome the selfish user impact.

关键词：

来源：评论

学校读者我要写书评

暂无评论

FedStar Caching: Decision Center Assisted Federated Cooperative Edge Caching

FedStar Caching: Decision Center Assisted Federated Cooperat...

引用

IEEE International Conference on Human-Machine systems

作者： Sirvan Gharib Mohammad Mansour Kesargheh S. Jamal Seyedmohammadi Zohreh Hajiakhondi Jamshid Abouei Konstantinos N. Plataniotis Dept. of Electrical Engineering Yazd University Yazd Iran Inst. of Information Systems Engineering Concordia University Montreal Canada Dept. of Electrical Engineering Concordia University Montreal Canada Dept. of Electrical and Computer Engineering University of Toronto Toronto Canada

ISBN: (数字)9798350315790

ISBN: (纸本)9798350315806

With the explosion of data, Wireless Edge Caching (WEC) has become a promising approach for locally accessing cached contents. Due to the limited storage capacity of local caching devices and the varying preferences of humans for content, it is necessary to predict popular contents. In this article, we will address two distinct objectives: 1) Popularity prediction of the content that should be cached at the edge to effectively utilize edge device memory. 2) Edge devices collaboration for efficient content delivery. Accordingly, we propose an FL-based Star Cooperative Caching (FedStar Caching), utilizing a Star network topology for realizing an efficient cooperation among Femto-cell Access Points (FAPs) using a Decision Center (DC) to enhance power efficiency and delay performance. Considering human sensitivity to privacy, collecting users’ data on a central server is not desirable, therefore, we leverage Federated Learning (FL) to alleviate this challenge. Simulation results demonstrate that the proposed method outperforms alternatives in terms of cache efficiency, as well as delay and power consumption.

关键词： Wireless communication Wireless sensor networks Power demand network topology Cooperative caching Simulation Stars

来源：评论

学校读者我要写书评

暂无评论

Weapon detection system for surveillance and security

Weapon detection system for surveillance and security

引用

2023 International Conference on IT Innovation and Knowledge Discovery, ITIKD 2023

作者： Khalid, Shehzad Waqar, Abdullah Ain Tahir, Hoor Ul Edo, Onome Christopher Tenebe, Imokhai Theophilus Bahria University Dept. of Computer Engineering Islamabad Pakistan Auburn University at Montgomery Department of Information Systems Alabama United States Mineta Transportation Institute San Jose State University CA United States

ISBN: (纸本)9781665463720

Weapon detection is a critical and serious topic in terms of public security and safety, however, it's a difficult and time-consuming operation. Due to the increase in demand for security, safety, and personal property protection, the requirement for deploying video surveillance systems capable of recognizing and interpreting scenes and anomalous occurrences plays an important role in intelligence monitoring. In certain regions of the globe, mass shootings and gun violence are on the increase. Timely detection of the presence of a gun is critical to prevent loss of life and property. Several object detection models are available, which struggle to recognize firearms due to their unique size and form, as well as the varied colors of the background. In this study, we proposed a state-of-the-art system based on a deep learning model YOLO V5 for weapon detection that will be sufficiently resilient in terms of affine, rotation, occlusion, and size. We evaluated the performance of our system on a publicly available dataset and achieved the F1-score of 95.43%. For the detection and segmentation of firearms, we implemented Instance segmentation or Pixel level segmentation which employed Mask-RCNN. The system achieved the detection accuracy (DC) of 90.66% and 88.74% Mean intersection over union (mIoU). The purposed methodology combined different data augmentation and preprocessing methods to improve the accuracy of the proposed weapon detection system. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Coordinate Attention-enabled Ship Object Detection with Electro-optical Image 11

Coordinate Attention-enabled Ship Object Detection with Elec...

引用

11th International Conference on Computing and Pattern Recognition, ICCPR 2022

作者： Xu, Hongbin Jiang, Xiantao Yin, Tao Cen, Qi Zhang, Zhijian Song, Tian Yu, F. Richard Dept.Information Engineering Shanghai Maritime University Shanghai China Ningbo Special Equipment Inpection and Research Institute Ningbo China Dept. Electrical and Electronics Engineering Tokushima University Tokushima Japan Dept. Systems and Computer Engineering Carleton University Ottawa Canada

ISBN: (纸本)9781450397056

Shipping safety is one of the factors restricting the development of navigation. In particular, the route near the shore is prone to unknown risks due to the existence of multiple types of ships, the density of ships, the shielding between ships, and other reasons. This paper presents a method for detecting medium-range ships, which can improve security for ships. This method is based on the You Only Look Once Version 5 network (YOLOv5). To improve the accuracy, the coordinate attention model is integrated into the detection network. The main research content and experimental work of this paper are as follows. Firstly, the YOLOv5 network and spatial attention mechanism are analyzed. Then, detection experiments were carried out based on YOLOv5 and Singapore Maritime Data Set (SMD). Then, the coordinate attention model was used to improve the network. Finally, by adjusting training parameters and improving attention, the mAP of test results of the object detection network reaches 73%, and the feasibility of object detection of the YOLOv5 algorithm with coordinate attention is confirmed. © 2022 ACM.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Device Identification using network Traces in a Smart Home IoT network

Device Identification using Network Traces in a Smart Home I...

引用

International Symposium on Advanced networks and Telecommunication systems (ANTS)

作者： Jwngfu Brahma Rakesh Matam Nikumani Choudhury Dept. of Computer Science & Engineering Indian Institute of Information Technology Guwahati India Dept. of Computer Science & Information Systems Birla Institute of Technology & Science Hyderabad India

Device identification is a crucial aspect of securing networks, particularly in the context of the Internet of Things (IoT), where a vast variety of devices are interconnected. Recently, there has been significant research on developing techniques for identifying IoT devices based on their unique characteristics, called as device fingerprints. These techniques use machine learning algorithms, which can effectively learn and classify devices based on their features. However, device identification remains a challenging task due to the diversity of IoT devices and the constant evolution of their characteristics. This paper presents our attempt at device identification by analyzing distinct device characteristics observed during network communication and using different machine learning techniques.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Threat Model for Autonomous Vehicle Communication security

A Comprehensive Threat Model for Autonomous Vehicle Communic...

引用

Advancements in Computing (ICAC), International Conference on

作者： Niranjan W. Meegammana Harinda Fernando Cyber Security Research Lab Shilpa Sayura Foundation Kandy Sri Lanka Dept. of Computer Systems Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798331517878

ISBN: (纸本)9798331517885

The rapid advancement of autonomous vehicles (AVs) promises to enhance transportation efficiency, reliability, and safety. However, these systems, particularly multi-channel vehicular communications, are vulnerable to cyber attacks that threaten authenticity, authorization, confidentiality, integrity, availability, and non-repudiation. The 2014 Chrysler Jeep hack highlights the urgent need for robust security measures in vehic-ular communications. This study utilizes the STRIDE, DREAD, and MITRE ATT&CK security frameworks to develop a comprehensive threat model that identifies and assesses critical threats and risks to AV communications. By detailing specific attack vectors and their multidimensional impacts and criticality, the study establishes a baseline of threats for communication security in vehicular networks. It produces visual threat maps, impact graphs of various attacks, and a color-coded threat grid to guide stakeholders in developing effective cyber security measures for protecting AV communications, thereby help stakeholders to improve the reliability and safety of AV navigation for fostering growth in the AV industry.

关键词： Threat modeling Visualization Transportation Sensor fusion Vectors Safety security Stakeholders Reliability Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Advancements in Jute Leaf Disease Detection: A Comprehensive Study Utilizing Machine Learning and Deep Learning Techniques

Advancements in Jute Leaf Disease Detection: A Comprehensive...

引用

Power, Electrical, and Electronics and Industrial Applications (PEEIACON), IEEE International Conference on

作者： Rezaul Haque Md Miraz Miah Shayma Sultana Hasib Fardin Abdullah Al Noman Abdullah Al-Sakib Md Kamrul Hasan Al Rafy Rahman Md Shihabur Shafiur Rahman Dept. of CSE East West University Dhaka Bangladesh Dept. of CSE BRAC University Dhaka Bangladesh Dept. of Management Information System International American University CA USA Dept. of Engineering Management Westcliff University CA USA Dept. of Information Technology Westcliff University CA USA Dept. of Cyber security Touro University CA USA Dept. of Computer Engineering Kyungdong University Gangwon-do Republic of Korea Dept. of Software Engineering Daffodil International University Dhaka Bangladesh

ISBN: (数字)9798331517984

ISBN: (纸本)9798331517991

Detecting diseases in jute leaves is difficult due to the variability in how the diseases appear. Manually identifying these diseases is challenging because it requires expert knowledge and visual inspections take a lot of time. Machine Learning (ML) offers a promising solution to these challenges by automating the detection process. However, research in this area is limited due to the lack of specific datasets. This study aims to address this by creating a comprehensive dataset of 10,800 high-quality images of jute leaf diseases. The main goal is to develop a robust system for classifying jute leaves into three categories: Yellow Mosaic, Powdery Mildew, and Healthy. Our methodology involved extensive image preprocessing, including resizing and various augmentation techniques, to enhance the dataset's diversity and ensure model robustness. We trained various ML and Deep Learning (DL) models and conducted a comparative analysis of their performance. Additionally, we compared our approach with the state-of-the-art methods. The results showed that DL models, particularly Inception V3, achieved an outstanding accuracy of 99.98\%, compared to 89.75\% for Random Forest (RF). This highlights the potential of DL techniques in improving the accuracy of jute leaf disease detection. Our findings contribute to better disease management strategies and increased productivity in jute cultivation.

关键词： Deep learning Radio frequency Analytical models Visualization Accuracy Transfer learning Robustness Real-time systems Random forests Diseases

来源：评论

学校读者我要写书评

暂无评论

Secure data exchange system in software-defined networks of energy complex facilities

Secure data exchange system in software-defined networks of ...

引用

2021 International Conference on Electrotechnical Complexes and systems, ICOECS 2021

作者： Khayretdinov, Rinat Dautov, Damir Vulfin, Alexey Mironov, Konstantin Frid, Arkadij Ufa State Aviation Technical University Dept. of Computer Engineering and Information Security Ufa Russia

ISBN: (纸本)9781665407274

The analysis of threats to information security breaches was carried out and the corresponding countermeasures were provided by the levels of the SDN architecture. Tools (algorithms, software and architecture of the interaction system) to protect the control traffic of software-defined networks were developed and implemented. A method based on the introduction of an encrypted label into the packet header was proposed, allowing for recognition of malicious traffic between SDN nodes. If the label is invalid, the packet is dropped without further processing. The ability to detect packets sent to an SDN controller by an attacker was demonstrated. Thus, the effectiveness of countering DoS attacks increased by 7.8 times. Further development of the proposed approach involves creation of a software and hardware module for embedding in SDN switching equipment. © 2021 IEEE.

关键词： Denial-of-service attack

来源：评论

学校读者我要写书评

暂无评论

Macula Swelling Detection using Retinal Fundus Images

Macula Swelling Detection using Retinal Fundus Images

引用

IEEE International Workshop on Imaging systems and Techniques (IST)

作者： Rukham Mumtaz Khan Fazal Saadat Ali Khan Fauzia Khan Rafia Hassan Dept. of Computer Engineering National University of Sciences and Technology Islamabad Pakistan Dept. of Information Security National University of Sciences and Technology Islamabad Pakistan Dept. of Computer Science University of Tartu Tartu Estonia Dept. of Software Engineering Bahria University Islamabad Pakistan

Diabetic Macular Edema (DME) is an advanced symptom of Diabetic Retinopathy (DR) and can lead to irreversible vision loss. Macular Edema (ME) is the swelling of the macula, the part of the eye accountable for thorough central vision. The utilization of image processing in the detection of diabetic macular edema (DME) plays a crucial role in the field of medical imaging, effectively reducing the time and manual effort required by medical specialists to identify this disease. In this paper, we proposed a method that uses digital fundus images to analyze the swelling of the macula. The proposed algorithm consists of four steps, i.e., (i) retinal image dataset collection, (ii) retinal image pre-processing, (iii) feature extraction, and (iv) classification to categorize the disease into three different stages, i.e., normal, stage 1 (mild) and stage 2 (severe). The proposed method is tested on three databases, i.e., MESSIDOR, DMED, and the local dataset AFIO obtained from the local hospital in Pakistan. We use three parameters to check the validity of the proposed algorithm, i.e., visual inspection, accuracy, and area under calculation time. Our method achieves an average accuracy of 96.07 % with a sensitivity of 93.74 % and specificity of 97.32%. We also compare our results with other proposed methods, which shows our method performs better.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Using AI and Natural Language Processing to Enhance Consumer Banking Decision-Making

Using AI and Natural Language Processing to Enhance Consumer...

引用

2024 International Conference on E-Mobility, Power Control and Smart systems, ICEMPS 2024

作者： Temara, Sheetal Samanthapudi, Sagar Varma Rohella, Piyush Gupta, Ketan Ashokkumar, S.R. University of The Cumberlands Dept of Computer & Information Sciences WilliamsburgKY United States The Polis Center Indiana University Purdue University Indianapolis Applied Data Science IndianapolisIN United States Payments & Commerce GoDaddy EdmondsWA United States University of The Cumberlands Dept. of Information Technology WilliamsburgKY United States Sri Eshwar College of Engineering Centre For Blockchain and Cyber Security Department of Computer and Communication Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350394399

This technical summary outlines the use of Artificial Intelligence (AI) and Natural Language Processing (NLP) to beautify patron banking decision-making. AI-based banking systems can autonomously identify patterns in consumer information and generate insights from a number of sources, including but not restricted to purchaser 360 profiles, 1/3-party statistics, and transactional statistics. With the assistance of AI and NLP, this gadget can answer customer questions relating to their banking wishes and offer personalized recommendations. AI-based monetary decision-making systems also permit banks to offer computerized customer service with information on clients' needs, respond speedily to purchaser requests, and offer quick acclaim for loans and other banking merchandise. Moreover, AI and NLP enhance patron engagement via chatbot-like solutions and purchaser sentiment analysis. The extraordinary AI and NLP-based services being presented by using banks are mentioned in this technical abstract. In conclusion, AI and NLP technology are giving banks the capacity to meet the desires of their customers and improve typical purchaser pleasure. © 2024 IEEE.

关键词： Artificial intelligence

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57页 << < 6 7 8 9 10 11 12 13 14 15 > >>

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：