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

1,779 篇 会议
12 篇 期刊文献
9 册 图书

馆藏范围

1,800 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,027 篇 工学
- 658 篇 计算机科学与技术...
- 457 篇 软件工程
- 314 篇 控制科学与工程
- 207 篇 环境科学与工程（可...
- 193 篇 电气工程
- 192 篇 信息与通信工程
- 150 篇 动力工程及工程热...
- 146 篇 化学工程与技术
- 109 篇 机械工程
- 91 篇 土木工程
- 88 篇 仪器科学与技术
- 78 篇 电子科学与技术（可...
- 71 篇 农业工程
- 63 篇 建筑学
- 63 篇 安全科学与工程
- 62 篇 水利工程
- 51 篇 交通运输工程
- 45 篇 材料科学与工程（可...
- 42 篇 石油与天然气工程
- 40 篇 力学（可授工学、理...
376 篇 理学
- 142 篇 化学
- 128 篇 数学
- 90 篇 物理学
- 42 篇 生物学
- 37 篇 统计学（可授理学、...
221 篇 管理学
- 186 篇 管理科学与工程(可...
- 79 篇 工商管理
- 56 篇 图书情报与档案管...
70 篇 农学
- 62 篇 作物学
33 篇 医学
29 篇 经济学
17 篇 法学
6 篇 教育学
6 篇 军事学
2 篇 文学
1 篇 艺术学

主题

288 篇 monitoring
109 篇 wireless sensor ...
92 篇 distributed cont...
77 篇 internet of thin...
77 篇 control systems
74 篇 computers
72 篇 computer archite...
71 篇 real-time system...
70 篇 intelligent sens...
51 篇 temperature sens...
42 篇 sensor systems
42 篇 environmental ma...
38 篇 intelligent netw...
35 篇 environmental mo...
35 篇 sensors
34 篇 cloud computing
33 篇 computerized mon...
31 篇 computer network...
29 篇 distributed comp...
27 篇 robot sensing sy...

机构

10 篇 school of munici...
7 篇 chinese research...
6 篇 changsha univers...
6 篇 school of energy...
6 篇 school of civil ...
5 篇 department of en...
5 篇 faculty of envir...
4 篇 college of envir...
4 篇 school of automa...
4 篇 raj kumar goel i...
4 篇 college of envir...
4 篇 univ politehn bu...
4 篇 school of comput...
4 篇 shanghai univers...
4 篇 school of enviro...
4 篇 de la salle univ...
4 篇 de la salle univ...
4 篇 department of en...
4 篇 school of enviro...
4 篇 chongqing electr...

作者

5 篇 concepcion ronni...
5 篇 li xu
4 篇 zhu yinian
4 篇 wang jian
4 篇 zhang yan
4 篇 wu jinxiang
4 篇 bandala argel
4 篇 wang ying
4 篇 liu chang
4 篇 liu jian
3 篇 ahmad jalal
3 篇 hui wang
3 篇 yang jun
3 篇 mariana mocanu
3 篇 wang xiaojun
3 篇 wang juan
3 篇 malik praveen ku...
3 篇 m. mutka
3 篇 weiyao zhu
3 篇 mocanu mariana

语言

1,757 篇 英文
39 篇 其他
6 篇 中文
1 篇 西班牙文

检索条件"任意字段=International Conference on Computer Distributed Control and Intelligent Environmental Monitoring"

共 1800 条记录，以下是331-340 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：

Collective Decision-Making and Change Detection with Bayesian Robots in Dynamic Environments

Collective Decision-Making and Change Detection with Bayesia...

引用

IEEE/RSJ international conference on intelligent Robots and Systems (IROS)

作者： Kai Pfister Heiko Hamann Institute of Computer Engineering University of Luebeck Germany Department of Computer and Information Science University of Konstanz Germany

Solving complex problems collectively with simple entities is a challenging task for swarm robotics. For the task of collective decision-making, robots decide based on local observations on the microscopic level to achieve consensus on the macroscopic level. We study this problem for a common benchmark of classifying distributed features in a binary dynamic environment. Our special focus is on environmental features that are dynamic as they change during the experiment. We present a control algorithm that uses sophisticated statistical change detection in combination with Bayesian robots to classify dynamic environments. The main profit is to reduce false positives allowing for improved speed and accuracy in decision-making. Supported by results from various simulated experiments, we introduce three feedback loops to balance speed and accuracy. In our benchmarks, we show the superiority of our new approach over previous works on Bayesian robots. Our approach of using change detection shows a more reliable detection of environmental changes. This enables the swarm to successfully classify even difficult environments (i.e., hard to detect differences between the binary features), while achieving faster and more accurate results in simpler environments.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Research on River Floating Objects Detection Method Based on Deep Learning

Research on River Floating Objects Detection Method Based on...

引用

computer, Vision and intelligent Technology (ICCVIT), international conference on

作者： Jiaqi Xu Yining Zhao Yuqi Cao Dibo Hou State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

The environmental issues have become increasingly prominent, and water environments have remained a major societal concern. Surface pollutants in rivers are one of the key factors damaging water environments. Given the large number and wide distribution of rivers, manual river inspections and the collection of floating objects are time-consuming and labor-intensive. In this study, a river surface floating objects detection method based on deep learning is proposed. To address the noise issues caused by interferences in natural scenes, an image preprocessing method based on median filtering and Laplace operator is studied. In order to select the most suitable deep learning algorithm, this work compares the YOLOv5, Faster-RCNN, and SSD algorithms. After comparative analysis, an optimized YOLOv5 model is proposed for detecting floating objects on river surfaces. Finally, a visualization platform is developed based on PyQt5, enabling real-time monitoring and display of floating objects in river surveillance videos. Experimental results demonstrate that this method can effectively detect floating objects on river surfaces, with recall rate of 0.741 for artificial trash, mAP@0.5 of 0.798, and mAP@0.5:0.95 of 0.704. This system achieves real-time surface floating objects monitoring in rivers and open channels, providing crucial information for the protection and management of water environments.

关键词： YOLO Deep learning Laplace equations Filtering Surface contamination Noise Real-time systems Water pollution Rivers Videos

来源：评论

学校读者我要写书评

暂无评论

Research on intelligent rabbit culture system based on Internet of things

Research on Intelligent rabbit culture system based on Inter...

引用

2021 international conference on Information Science, Parallel and distributed Systems, ISPDS 2021

作者： Liu, Yongxu Wu, Shuo Liu, Fei Zhao, Hong Meng, Zhen Qingdao Kangda Rabbit Industry Development Co. Ltd Qingdao China EDP Qingdao Kangda Rabbit Industry Development Co. Ltd Qingdao China

ISBN: (纸本)9781665417389

In view of the problems in the development of livestock and poultry breeding industry in China, such as tight constraints on production resources, rising costs, livestock and poultry epidemic, product quality and safety, environmental pollution, this study proposed a smart meat rabbit breeding system based on Internet of things technology for medium and large-scale meat rabbit farms and small-scale breeding investors. Through the monitoring of breeding environmental factors and the control of equipment, we can achieve fine feeding, disease early warning and scientific breeding, improve production efficiency and reduce breeding risk. © 2021 IEEE.

关键词： Disease control

来源：评论

学校读者我要写书评

暂无评论

Interplay of Remote Sensing and Artificial Intelligence in Open Agricultural Land monitoring 15

Interplay of Remote Sensing and Artificial Intelligence in O...

引用

15th IEEE international conference on Humanoid, Nanotechnology, Information Technology, Communication and control, Environment, and Management, HNICEM 2023

作者： Almalbis, Anya Eliza Y. Gochian, Alexandra Brianne B. Murillo, Raphael C. Uy, Alexandra Dominique M. Concepcion, Ronnie Valencia, Immanuel Jose Bandala, Argel De la Salle University - Integrated School Department of Science Technology Engineering and Mathematics Manila Philippines De la Salle University Department of Manufacturing Engineering and Management Manila Philippines De la Salle University Department of Electronics and Computer Engineering Manila Philippines

ISBN: (纸本)9798350381177

As a prominent global player in rice production, the Philippines has consistently upheld its commitment to ensuring food security and meeting the demands of its population. This was highly evident in the year 2021 when the nation achieved a milestone by yielding a harvest of 19.96 million metric tons of rice. However, due to its geographical location in Southeast Asia and its influence on global warming, the country is highly susceptible to the devastating effects of tropical cyclones. Climate change, particularly the rise in global temperatures, makes oceans heat up more. This leads to an increase in the frequency and intensity of weather events that pose a significant threat to the agricultural sector and profoundly impact the livelihood of farmers who heavily rely on crops. Several studies collectively aimed to assess the impact of crop losses on agricultural fields, particularly areas prone to natural disasters. These studies utilized diverse methodologies that comprehensively evaluated the impact of these disasters on crop fields and the economic losses in the area, therefore providing significant insights into environmental factors and agricultural productivity in farming areas. The methodologies employed in these studies focused on improving crop prediction through data analysis techniques. Machine learning approaches like Support Vector Machines and Decision Tree algorithms were utilized in enhancing the efficiency of crop management. Data collection was gathered from diverse sources like government websites. While technology-driven approaches like data logging, satellite imagery, and machine learning were used to locate and map crop production stages. © 2023 IEEE.

关键词： Crops

来源：评论

学校读者我要写书评

暂无评论

Research on Vehicle Safety Models for Urban Roads

Research on Vehicle Safety Models for Urban Roads

引用

Electronic Information Engineering and computer Communication (EIECC), international conference on

作者： Yingying Zhuo Yongjie Zhang Education Department of Guangxi Zhuang Autonomous Region GuangXi Vocational Normal University China Guangxi Nanning Xixiangtang District Luowen Avenue 17 Key Laboratory of Application Technology of Intelligent Connected Vehicle (Guangxi Vocational Normal University) Guangxi China

ISBN: (数字)9798331534622

ISBN: (纸本)9798331534639

In this paper, an efficient safety model is constructed for the safety of driverless vehicles on urban roads. By analyzing the current situation of traffic accidents, it points out that weather, geography, and human flow are uncontrollable risk sources. To this end, the model integrates vehicle-road cooperative sensing technology, fuses intelligent decision warning and collision time braking mechanism, and significantly improves road safety. Using Prescan simulation and Matlab cross-validation, the model monitors traffic flow, vehicle status, environmental conditions, and warns of potential risks in real time. Through advanced algorithmic analysis, it evaluates traffic management strategies such as signal light control and speed limit measures to optimize traffic flow and enhance safety. The model can automatically intervene at critical moments to create a safer environment for drivers and passengers, and is widely used in automotive and urban road traffic safety systems.

关键词： Roads Mathematical models Road traffic Real-time systems Safety Sensors Security MATLAB monitoring Meteorology

来源：评论

学校读者我要写书评

暂无评论

Study of Ocean Pattern's and Ocean Bed Using Applications of IOT

Study of Ocean Pattern's and Ocean Bed Using Applications of...

引用

Emerging Trends in Information Technology and Engineering (ic-ETITE), conference on

作者： K Vishwanath Rachit Reddy Sritama Roy Department of Computer Science Vellore Institute of Technology Chennai India School of Electronics Engineering Vellore Institute of Technology Chennai India

The ocean plays an integral role for influencing Earth's climate and sustaining diverse ecosystems as oceans covers almost 70 % of the earth's surface. It is important to monitor and control the ocean biodiversity through the advanced IoT technologies. The internet of Underwater things (IoUT) is an emerging technology which can connect the underwater objects as well as environment. IoUT is directly related with the navigation, disaster prediction, smart monitoring and intelligent system. Understanding the dynamics of the ocean is crucial for various applications, including weather forecasting, maritime operations, and environmental conservation. This research paper presents an in-depth analysis of an Ocean buoy monitoring System that utilizes temperature, humidity, and geolocation data collected from buoys to predict ocean patterns, tides, and marine life. The system combines real-time sensor measurements with advanced data analysis techniques to provide valuable insights into oceanographic phenomena.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Design of RTOS-based Wireless Remote monitoring System for Indoor Environment 23

Design of RTOS-based Wireless Remote Monitoring System for I...

引用

Proceedings of the 2023 12th international conference on Networks, Communication and Computing

作者： Peizhi Zhu Dajun Li Lihui Guo Fanqiang Lin Chengdu University of Technology China

ISBN: (纸本)9798400709265

With the development of low-cost microcontrollers, sensors and wireless communications, intelligent environment monitoring based on the Internet of Things (IoT) has become possible. In this paper, an indoor environment monitoring system constructed by sensor network is realized. The system consists of distributed sensing nodes, which contain temperature and humidity, human infrared, voice recognition and camera sensors, etc. The nodes are connected to STM32 microcontrollers and WIFI modules and are scheduled in real time using free real time operating system(FreeRTOS). The visual and time series sensing data are transmitted to the server via WIFI in real time, and the user can monitor the system remotely by using the PYQT interface program on the PC. The system can also control home appliances by voice. The data interaction uses self-built WIFI module in AP mode for SOCKET communication. Through rigorous testing, the system demonstrates the capability of data communication, low-latency video streaming, and bi-directional control. The sensor network and real-time OS based architecture utilizes parallel execution to balance different temporal tasks and realize an agile cyber-physical system. This paper provides a reference for the underlying software infrastructure of intelligent buildings, embodying the integrated application of real-time scheduling, sensor networks and human-computer interaction.

关键词： Internet of Things Real Time Operating System STM32 data acquisition Sensor networks WIFI

来源：评论

学校读者我要写书评

暂无评论

An intelligent Dipsomania Face Detection Model using Spatial and Spectral Graph Neural Network

An Intelligent Dipsomania Face Detection Model using Spatial...

引用

Smart Electronics and Communication (ICOSEC), international conference on

作者： N Madhusundar R Surendran S Johnpaul K Appathurai Department of Computer Science and Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Information Technology Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College Chennai India Department of Computer Technology KG College of Arts and Science Coimbatore India

ISBN: (数字)9798331504403

ISBN: (纸本)9798331504410

Dipsomania, alcohol addiction that is out of control poses serious problems for public health. Conventional techniques for identifying drunk people depend on behavioral indicators, which are easily manipulated. This article suggests a novel method by employing spectral and spatial graph neural networks (SS-GNN) to create an intelligent face identification model for dipsomania. Facial traits are stored as nodes and edges in a graph structure, and the model uses the special powers of graph neural networks to process and analyses these features. The SS-GNN model that has been suggested is trained on a wide range of facial image datasets that include both drunken and sober states. Advanced methods of data augmentation and domain adaptation are utilized to enhance the model’s resilience and applicability to various demographics and environmental circumstances. By combining spectral and spatial information into a graph-based framework, dipsomania-related facial traits can be better understood. This innovative method provides a noninvasive, dependable means of early diagnosis and intervention in cases of alcohol addiction and shows potential for real-time applications in public safety, healthcare, and workplace monitoring.

关键词： Adaptation models Addiction Alcoholism Feature extraction Graph neural networks Real-time systems Face detection monitoring Faces Resilience

来源：评论

学校读者我要写书评

暂无评论

Empirical Evaluation of Internet of Things Assisted Fire Fighting Robotic Design Based on intelligent Sensors Association

Empirical Evaluation of Internet of Things Assisted Fire Fig...

引用

Electronics and Sustainable Communication Systems (ICESC), 2020 international conference on

作者： T Mahitha Sajja Suneel M. Amina Begum Er. S. John Pimo B. Swapna Revathi. R Department of Computer Science Saveetha College of Liberal Arts and Sciences SIMATS Department of CSE(Data Science) Institute of Aeronautical Engineering Hyderabad Telangana India Department of ECE Oxford College of Engineering Venmani Tamilnadu India Computer Science and Engineering St. Xavier's Catholic College of Engineering Nagercoil ECE Dr MGR Educational and Research Institute Chennai Department of Computer Science Karpagam Academy Of Higher Education Coimbatore

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379952

This research work presents the design and implementation of an Internet of Things (IoT) assisted fire fighting robotic system based on intelligent sensors association. The system integrates various components including intelligent sensors for detecting fire, smoke, temperature changes, and gas emissions, Arduino microcontrollers for data processing and control logic execution, Wi-Fi communication modules for remote monitoring and data exchange, and actuators for physical motion and manipulation tasks. Through the integration and coordination of these components, the firefighting robot achieves autonomous capabilities in detecting, localizing, and responding to fire incidents effectively. The intelligent sensors, including the MQ-2 Gas Sensor, TMP36 Temperature Sensor, MQ-7 Carbon Monoxide Sensor, and MLX90614 Non-Contact Infrared Temperature Sensor, provide real-time environmental data inputs to the Arduino Uno microcontroller, which interprets sensor readings, executes decision-making algorithms, and orchestrates responses. Leveraging bidirectional Wi-Fi connectivity facilitated by the ESP8266 Wi-Fi Module, the system enables remote monitoring and data exchange, empowering operators with situational awareness for informed decision-making. Actuators such as DC Gear Motors and SG90 Micro Servo Motors translate digital commands into mechanical motion and manipulation, enabling the robot to navigate through fire-affected environments, manipulate fire fighting tools, and execute precision fire fighting maneuvers. This abstract presents a comprehensive overview of the IoT-assisted fire fighting robotic system, highlighting its autonomous capabilities, integration of components, and potential for enhancing fire fighting efficiency and safety.

关键词： Temperature sensors Actuators Microcontrollers Robot kinematics Decision making Robot sensing systems Internet of Things intelligent sensors Wireless fidelity Remote monitoring

来源：评论

学校读者我要写书评

暂无评论

Digitalization of Integrated Industrial IoT Technologies for monitoring and Cloud Analytics in Sustainable Horticultural Practices

Digitalization of Integrated Industrial IoT Technologies for...

引用

intelligent control, Computing and Communications (IC3), international conference on

作者： Praveen Kumar Malik Veena Bharti Shailendra Thapliyal Jaypal Lande Anshul Mahajan Parulpreet Singh School of Electronics and Electrical Engineering Lovely Professional University Phagwara Punjab India Raj Kumar Goel Institute of Technology Ghaziabad India Uttaranchal Institute of Magagement Uttaranchal University Dehradun Uttarakhand India School of Computer Science & Artificial Intelligence SR University Warangal

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

Agriculture has been one of the most important areas that human being has to rely on but due to ever rising global population and ecological crises, there is an increasing demand for ecological farming techniques. Industry 4.0 is the latest evolution of industries that integrates tools such as IoT, AI, and big data and has the potential to transform agriculture. These technologies allow for precise agriculture, resource management, and better decisions to be made, catalyzing farming practices to be more eco-friendly and effective. One of the important limitations of modern farms is the ability to assess environmental attributes influencing plants' growth and yield. Most traditional techniques do not provide timely assessments and insights, which leads to excessive or insufficient use of inputs, especially water, fertilizers, and pesticides. This kind of mismanagement not only reduces the efficiency of agricultural output but also brings adverse effects to the surrounding nature. By employing digital systems that measure and evaluate state variables of the environment, farmers can intervene appropriately in the crop production process to improve plant health, conserve resources, and protect the environment.

关键词： Cloud computing Technological innovation Irrigation Adaptation models Crops Production Greenhouses Transforms Temperature control Farming

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180页 << < 30 31 32 33 34 35 36 37 38 39 > >>

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：