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

7,888 篇 会议
81 篇 期刊文献
76 册 图书

馆藏范围

8,045 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

5,021 篇 工学
- 3,891 篇 计算机科学与技术...
- 2,375 篇 信息与通信工程
- 1,786 篇 软件工程
- 1,352 篇 电气工程
- 629 篇 控制科学与工程
- 417 篇 动力工程及工程热...
- 368 篇 电子科学与技术（可...
- 313 篇 生物工程
- 220 篇 生物医学工程（可授...
- 206 篇 仪器科学与技术
- 203 篇 机械工程
- 173 篇 测绘科学与技术
- 161 篇 光学工程
- 125 篇 化学工程与技术
- 119 篇 材料科学与工程（可...
- 94 篇 建筑学
- 87 篇 土木工程
- 84 篇 安全科学与工程
- 83 篇 石油与天然气工程
1,364 篇 理学
- 627 篇 数学
- 404 篇 物理学
- 359 篇 生物学
- 213 篇 统计学（可授理学、...
- 138 篇 化学
- 121 篇 系统科学
681 篇 管理学
- 391 篇 管理科学与工程(可...
- 305 篇 图书情报与档案管...
- 147 篇 工商管理
236 篇 医学
- 208 篇 临床医学
- 130 篇 基础医学(可授医学...
83 篇 法学
81 篇 农学
57 篇 经济学
23 篇 军事学
20 篇 教育学
15 篇 文学
1 篇 哲学

主题

1,587 篇 wireless sensor ...
499 篇 neural networks
322 篇 wireless communi...
290 篇 convolutional ne...
247 篇 deep learning
237 篇 sensor nodes
221 篇 routing
215 篇 feature extracti...
181 篇 monitoring
179 篇 image processing
174 篇 signal processin...
173 篇 wireless sensor ...
168 篇 sensor networks
166 篇 energy consumpti...
164 篇 sensors
148 篇 accuracy
146 篇 sensor systems
141 篇 real-time system...
141 篇 protocols
141 篇 routing protocol...

机构

15 篇 chitkara univers...
10 篇 univ chinese aca...
10 篇 beijing universi...
10 篇 gla university m...
9 篇 south china univ...
9 篇 university of ch...
9 篇 beijing institut...
8 篇 school of inform...
8 篇 department of co...
8 篇 department of el...
7 篇 school of inform...
7 篇 chinese academy ...
6 篇 univ wisconsin d...
6 篇 karnataka bangal...
6 篇 computer network...
6 篇 shanghai jiao to...
6 篇 school of comput...
6 篇 school of electr...
6 篇 amrita vishwa vi...
6 篇 shihezi universi...

作者

12 篇 wang wei
11 篇 chen chen
9 篇 liu yang
9 篇 li qiang
8 篇 zhang tao
8 篇 wang lei
7 篇 wei liu
7 篇 liu wei
7 篇 cao jiannong
7 篇 wei wang
6 篇 badache nadjib
6 篇 jiao licheng
5 篇 zhou jie
5 篇 li xin
5 篇 hui wang
5 篇 pitchaimanickam ...
5 篇 soman k. p.
5 篇 liu ying
5 篇 zhang sheng
5 篇 qiang li

语言

7,910 篇 英文
125 篇 其他
18 篇 中文
1 篇 俄文

检索条件"任意字段=5th International Conference on Informational Processing in Sensor Networks"

共 8045 条记录，以下是41-50 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：

An Anomaly-Misuse Hybrid System for Efficient Intrusion Detection in Clustered Wireless sensor Network Using Neural Network 5th

An Anomaly-Misuse Hybrid System for Efficient Intrusion Dete...

引用

5th international conference on Computing Science, Communication and Security

作者： Nathiya, N. Rajan, C. Geetha, K. Dinesh, S. Aruna, S. Brinda, B. M. Paavai Coll Engn Namakkal Tamilnadu India KSR Coll Technol Thiruchengode Tamilnadu India Excel Engn Coll Komarapalayam Tamilnadu India

ISBN: (纸本)9783031751691;9783031751707

Wireless sensor networks (WSN) refer to a group of small self-sustaining processor-based systems which collect information from their sensors, produce a computation set, and data relayed to a Base Station. the nodes deployment is done over a range of environment types extending from harsh to hostile. the network's requirements vary depending on the environment type. WSNs must have self-sufficiency and autonomy in harsh environments. Whilst, security is crucial in hostile environments, where the WSNs must be trustworthy and secure. In order to reduce production costs and decrease power usage, the design of nodes in WSNs is typically very simple. sensor networks inherit all aspects of WSNs but also have their own unique features. thus, the WSN security model design is quite distinctive from that of Ad hoc networks. In hostile environments, an Intrusion Detection System (IDS) is very vital for WSNs as it has the ability to identify malicious network packets. IDS can be efficiently employed in numerous methods like Neural networks. Despite that, the classification algorithms must have the least cost of computation in resource-constrained environments. this work has proposed a novel clustering algorithm with an integrated IDS classifier using the modified Neural Network. the Neural Network structure can be optimized by the proposed System Mentoring-Learning-Based technique for detection of optimal cluster-heads, and enhancement of the intrusions' classification accuracy.

关键词： Wireless sensor networks (WSN) Intrusion Detection System (IDS) computational cost clustering algorithm with integrated IDS classifier using modified Neural Network and System Mentoring-Learning-Based technique

来源：评论

学校读者我要写书评

暂无评论

5th international conference on Computing and Network Communications, CoCoNet 2023

5th International Conference on Computing and Network Commun...

引用

5th international conference on Computing and Network Communications, CoCoNet 2023

ISBN: (纸本)9789819745395

the proceedings contain 44 papers. the special focus in this conference is on Computing and Network Communications. the topics include: Maximizing Efficiency: Unveiling the Potential of Kubernetes Metrics;resource-Aware Learning Automata for Low-Latency Task Scheduling in Fog Computing;Design of High Gain Wideband Petal-Shaped Magneto-Electric Dipole Metal Antenna for 5G Sub-6 GHz and Wi-Fi Applications;A Novel Billhook-Shaped 2-Element MIMO Array for Sub-6 GHz Millimeter Wave Application;energy-Efficient Transmission in Wireless sensor Network Using Compressive Sensing;smart City Solutions for Traffic Management;an IoT-Assisted Real-Time Urban Air Pollution Data Collection System;real-Time Stock Price Prediction Using Apache Kafka;RSS-Based Localization Using GRU and BiGRU Deep Learning Models in LoRaWAN-IoT networks;locating and Routing for IoT-Based Fire Evacuation System;an Energy-Efficient Data Management Approach Using Sparse Compression in Future-Ready IoT networks;a Framework for Developing IoT and Edge Computing-Based Smart Transportation Applications;a Mathematical Model for Data Traffic Management in Next-Generation IoT networks;crowdsourced Mobile Applications for Disaster Relief: A Case Study of Landslide Tracker and Amrita Kripa App Deployments in Sikkim Schools;design and Modeling of Modular Wheelchair for therapeutic Exercises;analyzing Data Traffic in IoT networks: A Novel Graph-Based Architecture;A Lightweight Privacy-Preserving and Authentication Model (LiPAM-FSG) for Fog-Based Smart Grids;time Series Analysis and Rule Mining for Detecting Industrial Control System Data Injection Attacks;Radius-Based Authentication: UFrames’ Novel Approach to Prevent Account Sharing;deep Neural Network-Based Secure Energy-Efficient Power Allocation in an Interference Network;An Adaptive Time Quantum-Based Efficient Round-Robin Algorithm for CPU Scheduling;low-Cost Advanced Undetectable Hardware-Based Malicious Keyboard;constructing a Blind Digital Signature Scheme

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Predictive Maintenance Platform for a Conveyor Motor sensor System Using Recurrent Neural networks 5th

A Predictive Maintenance Platform for a Conveyor Motor Senso...

引用

5th international conference on Neural Computing for Advanced Applications (NCAA)

作者： Kiangala, Kahiomba Sonia Wang, Zenghui Univ South Africa UNISA Dept Elect & Smart Syst Engn ZA-1709 Johannesburg Gauteng South Africa

ISBN: (纸本)9789819770007;9789819770014

Since the effusion of Industry 4.0 (I40) and smart manufacturing, predictive maintenance (PdM) has become critical to prevent severe system breakdowns and costly production downtime in various industries. Several state-of-the-art Artificial Intelligence (AI) approaches, such as machine learning models (ML), empower the PdM design concept to produce more accurate outcomes. In this study, we propose the development of a PdM platform that effectively detects future possible warnings and failures in the vibration speed sensor of a conveyor motor. We build the platform backend using recurrent neural networks (RNN) regression ML models to predict vibration speed values and their trends. We train our RNN models using univariate time-series historical vibration sensor data recorded over the years. the experimental results demonstrate the robustness of our platform built on RNN models compared to other traditional regression machine learning models such as Extreme Gradient Boosting (XGboost). We compare the effectiveness of the PdM platform with two RNN models: a basic RNN model and a long short-term memory (LSTM) model. Unlike other regression PdM systems focusing on predicting devices Remaining Useful Life (RUL), our PdM platform forecasts and generates new vibration sensor data based on the desired future time range. It also pinpoints set warning and failure values and indicates when these faults are more likely to occur. Factories can utilize this feature for analytics purposes.

关键词： Conveyor Motor sensor Predictive Maintenance (PdM) Recurrent Neural networks (RNN) Regression Models time-series data

来源：评论

学校读者我要写书评

暂无评论

CSGNet: A network with attention mechanism for automatic modulation recognition 5

CSGNet: A network with attention mechanism for automatic mod...

引用

5th international conference on Signal processing and Computer Science, SPCS 2024

作者： Li, Xianyi School of Control Science and Engineering Shandong University Shandong Jinan250002 China

ISBN: (数字)9781510686731

ISBN: (纸本)9781510686724

In this paper, a new network called CSGNet is introduced for automatic modulation recognition, designed to improve recognition accuracy in complex electromagnetic environments. this innovative network leverages the strengths of both Convolutional Neural networks (CNN) and Gate Recurrent Units (GRU) while mitigating their inherent weaknesses. Additionally, it incorporates a Self-Attention mechanism to further enhance its perceptual abilities. the primary advantage of this method is its superior recognition accuracy under low SNR conditions compared to traditional methods. the process starts by extracting basic I/Q data from the RadioML 2018.01a dataset as input. Subsequently, the CSGNet model performs an end-to-end modulation recognition task. the results demonstrate that this method excels at multiple SNR levels, highlighting the significant potential of deep learning in solving automatic modulation recognition challenges. this study underscores the effectiveness of integrating CNN, GRU, and Self-Attention mechanisms in enhancing the robustness and accuracy of modulation recognition systems. Furthermore, it demonstrates how deep learning techniques can be effectively applied to complex signal processing tasks. the findings suggest that CSGNet could be a valuable tool for improving communication systems, especially in challenging environments with low SNR. © 2025 SPIE.

关键词： Modulation Signal to noise ratio Feature extraction Deep learning Matrices Data modeling Machine learning Data processing Neural networks Quadrature amplitude modulation

来源：评论

学校读者我要写书评

暂无评论

Graph Neural Network-Based Malicious Node Detection to Improve the Security of Wireless sensor networks 5th

Graph Neural Network-Based Malicious Node Detection to Impro...

引用

5th international conference on Advances in Information Communication Technology and Computing, AICTC 2024

作者： Kumar, K. Khari, M. School of Computer and Systems Sciences Jawaharlal Nehru University New Delhi110067 India

ISBN: (纸本)9789819761050

Wireless sensor networks (WSNs) are designed with small and energy-efficient sensor nodes (SNs), which are made up of microcontroller and sensors, are a critical module, which is used to collect data and to perform computations. Numerous industries include these networks, for a variety of domains like health care, monitoring, eco-friendly, business, and martial operations. though Wireless sensor networks (WSNs) are widely used due to their ability to exchange large volumes of data, their extensive usage presents unique challenges. sensor nodes (SNs), which are the basic building blocks of WSNs, play a crucial role in addressing these challenges and ensuring efficient data transmission. To preclude information breaches and failure of network, security measures are crucial. Using Artificial Intelligence (AI) methods, such as Decision Tree (DT), Support Vector Machine (SVMs), Naïve Bayes (NB), and Random Forest (RF), for detection malicious nodes based on difference between predicted and real sensor readings is a good method to increase the security of WSN. In the real-time applications, SNs aspect for anomalies, and the base station performs classification using ML methods. Conversely, existing methods have limitations which include high false positive rate and inadequate sensitivity to detect offensive patterns. therefore, the authors deploy a Graph Neural Network (GNN)-based ML approach to detect malicious nodes in order to reduce these faults and enhance the Confidentiality, Integrity, and Availability (CIA) of networks. the proposed model revealed the outcomes, which have an accuracy rate of 98% and 98% for precision, recall, and F1 support. the model executes better than prior approaches, allowing to a relative investigation, which marks an important improvement in the security of WSNs in a diverse of applications. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Research on a MEMS pressure sensor for fast thermal runaway detection for lithium-ion batteries 5

Research on a MEMS pressure sensor for fast thermal runaway ...

引用

2024 5th international conference on Advanced Materials and Intelligent Manufacturing, ICAMIM 2024

作者： Wang, Shengqi Shi, Zhou Chen, Mingyang Han, Xiangguang Zhao, Libo Wang, Jiuhong School of Instrument Science and Technology Xi'an Jiaotong University Xi'an710049 China Hefei Gotion High-tech Power Energy Co. Ltd. Hanhui 230012 China

An absolute pressure sensor based on SOI (Silicon-on-insulator) substrate for thermal runaway detection of lithium-ion batteries is studied. A simulation and analysis of the stress distribution within the rectangular island-square membrane composite structure and the piezoresistor is conducted. A piezoresistive pressure sensor chip with a planar size of 2.5 × 2.5 mm is selected. Research on fabrication processing and packaging methods for the sensor is carried out. the test results demonstrate that the sensor exhibits an accuracy of ±0.2% FS within a pressure range of 50 to 250 kPa when working in a temperature range of -40~120℃. the sensor meets the demand for thermal runaway monitoring of power batteries. 2025 Published under licence by IOP Publishing Ltd.

关键词： Pressure sensors

来源：评论

学校读者我要写书评

暂无评论

Analyzing Data Traffic in IoT networks: A Novel Graph-Based Architecture 5th

Analyzing Data Traffic in IoT Networks: A Novel Graph-Based ...

引用

5th international conference on Computing and Network Communications, CoCoNet 2023

作者： George, Gemini Department of Computer Applications St. George’s College Aruvithura Erattupetta Kerala Kottayam686122 India

ISBN: (纸本)9789819745395

the rapid deployment of IoT networks in different industrial services has caused the emanation of a huge volume of data from sensors and monitors. the efficient analysis and compact representation of the big data generated are critical to managing its transfer, storage, and latency. In this work, we propose a novel graphical model that has the flexibility to adapt to different architectural features of distributed IoT systems with low-power sensors. Further, we consider the traffic load minimization problem in the network and map the problems of network coverage and clustering onto the graph to find an optimal distributed network structure that minimizes the traffic load. the proposed approaches are tested under different network conditions, and the simulation results emphasize the improved performance of the method. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Graph based architecture IoT Network construction sensor network

来源：评论

学校读者我要写书评

暂无评论

Energy-Efficient Transmission in Wireless sensor Network Using Compressive Sensing 5th

Energy-Efficient Transmission in Wireless Sensor Network Us...

引用

5th international conference on Computing and Network Communications, CoCoNet 2023

作者： Manuel, Ebin M. Darshana, A.P. Department of Electronics and Communication Rajiv Gandhi Institute of Technology Kottayam Kottayam India Department of Electronics and Communication College of Engineering Trivandrum Kerala Trivandrum India

ISBN: (纸本)9789819745395

Minimizing energy consumption and maximizing network longevity through efficient data transmission are open research problems in practical wireless sensor networks. the proposed work focuses on data transmission based on two methods: Compressive Sensing (CS) and Partial Canonical Identity matrix-based Compressive Sensing (PCI-CS). the performance of these two methods on different energy-efficient clustering and routing protocols, such as Low Energy Adaptive Clustering Hierarchy (LEACH), Stable Election Protocol (SEP), and threshold sensitive Energy-Efficient sensor Network (TEEN) is compared. the combination of CS or PCI-CS, along with these energy-efficient clustering and routing protocols, can immensely reduce energy consumption. Simulation results show that the PCI-CS method outperforms other methods in terms of energy efficiency as well as network longevity. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词：

来源：评论

学校读者我要写书评

暂无评论

sensor Embedding and Variant Transformer Graph networks for Multi-source Data Anomaly Detection 5th

Sensor Embedding and Variant Transformer Graph Networks for ...

引用

5th international conference on Neural Computing for Advanced Applications (NCAA)

作者： Ma, Liwei Huang, Zhe Peng, Bei Zhang, Mingquan He, Wangpeng Wang, Yu Xi An Jiao Tong Univ Sch Mech Engn Xian Peoples R China Wuhan Second Ship Design & Res Inst Wuhan Peoples R China Xidian Univ Sch Aerosp Sci & Technol Xian Peoples R China

ISBN: (纸本)9789819770007;9789819770014

With the rapid development of sensor technology and the proliferation of multi-source data, anomaly detection of multi-source time series data has become more and more important. In the past, anomaly detection methods often deal with the temporal information and spatial information contained in the data separately, which makes the spatio-temporal information in the data unable to be fully utilized by the model. To this end, this paper proposes a fusion of sensor embedding and temporal representation networks to solve this problem. In addition, we adopt graph neural network to better model multi-source heterogeneous data, and enhance the accuracy of anomaly detection by combining the double loss function of reconstruction loss and prediction loss. this approach not only facilitates the learning of normal behavior patterns from historical data but also enhances the model's predictive capabilities, allowing for more accurate anomaly detection. Experimental results on four multi-source sensor datasets show the superiority of the proposed method compared with the existing models. Further analysis show that the model enhances the interpretability of anomaly detection through the analysis of anomaly associated sensors.

关键词： multi-source time series anomaly detection graph neural network model interpretability

来源：评论

学校读者我要写书评

暂无评论

Defense Strategy Security Mechanism for sensor networks 5th

Defense Strategy Security Mechanism for Sensor Networks

引用

5th EAI international conference on Cognitive Computing and Cyber Physical Systems, IC4S 2024

作者： Nayak, Rakesh Shinde, Jitesh Gupta, Praveen Dash, Satyabrata Ghugar, Umashankar Singh, Lokendra Department of CSE OP Jindal University Raigarh India India Visakhapatnam India Uttrakhand Dehradun India Department of Computer Science and Engineering Jaipur National University Jaipur India

ISBN: (纸本)9783031770746

this paper examines the safety measures used in sensing unit networks, focusing on their effectiveness in securing critical applications from threats like unapproved access, information violations, and meddling. It assesses the current state of these devices, identifies their weaknesses and strengths, and identifies obstacles such as source restrictions, scalability, and ease of access to risks. the paper emphasizes the importance of cooperation and data sharing among countries in reinforcing protection technique safety devices. the review concludes with a call to action, emphasizing the need for continuous research, innovation, and policy frameworks to address the evolving security landscape and protect critical infrastructure. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Network intrusion

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500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：